#SQL BI Training video | Explore Tumblr posts and blogs

biittech · 12 days ago

Text

Best Online Computer Courses to Get a Job in 2025

The job market in 2025 is evolving rapidly, with technology driving the demand for digital skills across nearly every industry. Whether you're looking to switch careers, enhance your resume, or land your first tech job, online computer courses are an accessible and cost-effective way to become job-ready from the comfort of your home. In this post, we’ll explore the best online computer courses you can take in 2025 to boost your chances of getting hired.

Why Online Computer Courses Are in High Demand

With remote work now mainstream and businesses doubling down on digital transformation, technical skills are no longer optional—they're essential. Employers are seeking candidates who can contribute immediately, and those with verifiable, up-to-date computer skills often have a clear edge.

Online courses offer flexibility, real-world relevance, and the ability to learn from top institutions and experts without the need to attend a traditional classroom.

Criteria for Choosing the Right Online Course

Before enrolling, make sure the course meets a few essential criteria:

Industry Relevance: Is the course aligned with current job market trends?

Certification: Will you receive a certificate that is recognized by employers?

Instructor Quality: Are the instructors experienced in the field?

Support & Resources: Does the course offer community access, mentorship, or job placement assistance?

Choosing the right course isn't just about content—it's about outcomes.

Top Online Platforms Offering Job-Oriented Computer Courses

Several online platforms have distinguished themselves by consistently delivering high-quality, job-focused training:

1. Coursera

Coursera collaborates with top universities and tech companies to offer in-depth courses and full career certificates. Courses often include peer-reviewed assignments and real-world projects.

2. edX

Founded by Harvard and MIT, edX provides access to university-level content and professional certifications. It’s ideal for learners looking for both academic rigor and practical applications.

3. Udemy

Udemy offers affordable, on-demand video courses in a wide range of computer-related topics. With lifetime access, it’s perfect for self-paced learners.

4. LinkedIn Learning

LinkedIn Learning provides professionally curated courses in business, software, and creative skills, making it great for professionals looking to level up or pivot.

5. Google Career Certificates

Google’s certificate programs are designed to help learners acquire job-ready skills in high-demand fields like IT Support, Data Analytics, UX Design, and Project Management.

Best Computer Courses to Land a Job in 2025

Here are some of the most in-demand courses to help you land a tech job this year:

1. Data Science and Analytics

With data driving decision-making in every industry, skills in Python, R, SQL, and machine learning are incredibly valuable. Look for courses that include real-world projects and tools like Tableau or Power BI.

Recommended Course: IBM Data Science Professional Certificate (Coursera)

2. Artificial Intelligence and Machine Learning

AI and ML are no longer buzzwords—they're must-have skills. Learn neural networks, deep learning, and natural language processing to work in some of the most innovative tech fields.

Recommended Course: AI For Everyone by Andrew Ng (Coursera)

3. Cybersecurity

As cyberattacks grow more sophisticated, cybersecurity professionals are needed more than ever. Courses covering threat detection, risk analysis, and ethical hacking are especially valuable.

Recommended Course: Google Cybersecurity Certificate (Coursera)

4. Cloud Computing

Cloud platforms, such as AWS, Azure, and Google Cloud, are foundational to modern IT infrastructure. Certification in cloud computing opens doors to roles in architecture, DevOps, and system administration.

Recommended Course: AWS Certified Solutions Architect – Associate (Udemy)

5. Full Stack Web Development

Full-stack developers are skilled in both front-end and back-end technologies, making them highly employable. Key skills include HTML/CSS, JavaScript, React, Node.js, and databases like MongoDB.

Recommended Course: The Complete 2025 Web Development Bootcamp (Udemy)

6. DevOps and Software Engineering

DevOps engineers streamline software development and deployment processes. Skills in CI/CD, Docker, Kubernetes, and Git are highly sought after in tech companies.

Recommended Course: DevOps on AWS Specialization (Coursera)

7. UI/UX Design

Great design is crucial for user retention. Learn user research, wireframing, prototyping, and tools like Figma and Adobe XD to create user-centered digital products.

Recommended Course: Google UX Design Certificate (Coursera)

8. IT Support and Networking

A great entry point into the tech industry, IT support courses cover hardware, troubleshooting, networking, and system administration.

Recommended Course: Google IT Support Professional Certificate (Coursera)

Certifications That Boost Employability

Earning a well-known certification can significantly increase your credibility. Some of the most recognized include:

CompTIA A+/Security+

Cisco Certified Network Associate (CCNA)

AWS Certified Cloud Practitioner

Google Career Certificates

Microsoft Azure Fundamentals

Pair these with hands-on experience or projects, and your resume will stand out in any applicant pool.

Tips for Maximizing Success in Online Learning

To get the most out of your online course, treat it like a professional commitment:

Set a Study Schedule: Stick to consistent hours each week.

Engage Actively: Participate in forums, ask questions, and collaborate.

Apply What You Learn: Build projects, contribute to open-source, or freelance.

Track Your Progress: Use LinkedIn or a portfolio site to showcase certifications and projects.

Final Thoughts: Take the Leap into Tech

Tech skills are the currency of the modern job market. With the right online computer course, you can future-proof your career and gain the confidence to land a job in 2025. Whether you're starting from scratch or upskilling, there's never been a better time to learn, grow, and go after the job you want.

Ready to get started? Let me know if you'd like help picking the right course or building your learning roadmap!

#online computer course #Online Learning #Best Computer Courses #demand for digital skills

0 notes

360edukraft · 1 month ago

Text

Which is the Best Microsoft Power BI Training Institute in Bangalore?

Introduction: The Rise of Data-Driven Decision Making

In today's hyper-connected business world, numbers speak. But data, by itself, is mere noise unless interpreted as insights. That's where business intelligence (BI) tools like Microsoft Power BI step in—turning intricate data into persuasive visuals and stories.

Why Power BI Has Become the Gold Standard for Business Intelligence

With interactive dashboards, real-time analysis, and seamless integration with Microsoft products, Power BI is the crown jewel of the BI category. As a Fortune 500 firm or startup, Power BI empowers organizations with the ability to take action on insights, not just data.

What Makes a Power BI Certification Worthwhile?

A certification not only confirms your technical skill but also betrays your seriousness towards the profession. A 1 Power BI Certification Training Course in Bangalore ensures that you're not learning the tool, but using it strategically in real-world situations.

Key Aspects of a High-Standard Power BI Training Institute

High-quality institutes don't just exist in theory. Look for these standards:

Hands-on labs and simulations

Capstone projects on actual data sets

Industry-veteran subject matter experts as trainers

Mock interviews and resume building

Active placement assistance

What to Expect in a Power BI Certification Training Course in Bangalore

A standard course in Bangalore consists of modules such as:

Data Modeling and DAX

Power Query and ETL processes

Custom visuals and dashboards

Integrating Power BI with Excel, Azure, and SQL Server

Live projects with Bangalore-based companies

Bangalore: The IT Capital Breeding Data Analysts

Why is Bangalore so hot for BI training? It's the Indian Silicon Valley. With thousands of MNCs, start-ups, and technology parks, innovation is palpable in the city. Institutes here tend to work directly with firms for latest learning modules.

Measuring the Best Institutes in Bangalore – Factors to Look Out For

Before you enroll, evaluate each institute on:

Trainer qualifications

Success rate of alumni

Relevance of course material

Partnerships with industries

Testimonials from previous students

Top 5 Power BI Training Institutes in Bangalore

Institute 1: Features, Fees, Reviews, and Placement Stats

100+ hours of training

Weekend as well as weekday batches

Corporate collaborations with IT giants

Placement support with 90% success rate

Institute 2: What Makes It Different

Intensive emphasis on DAX and advanced analysis

Job-relevant capstone projects

Guidance by Microsoft-certified professionals

Institute 3: Learning Culture and Support

24/7 doubt clarification support

Access to a global peer group

Recorded classes for flexibility during revision

Institute 4: Freshers' Success Stories and Career Successes

Success stories of hiring freshers at INR 6–9 LPA

Transformatory feedback by professionals at work

Detailed case studies as instructional aids

Institute 5: Flexibility, Modules, and Certification Route

Self-paced + instructor-led

Modules updated quarterly

Industry-approved certificate with Microsoft labeling

Comparing Power BI Certification Training Course in Bangalore vs Pune vs Mumbai

Power BI Certification Training Course in Pune offers excellent content, but fewer tech tie-ups.

Power BI Certification Training Course in Mumbai leans toward finance/data analytics in BFSI sectors. Bangalore wins for diversity in project exposure and MNC presence.

Why Bangalore Provides an Advantage Over Other Cities

It's not about learning—it's about opportunities after learning. With the sheer number of tech firms in Bangalore, there are more interviews, more networking sessions, and quicker professional growth.

Online vs Offline Training – What is Best in 2025

Whereas offline provides human touch and discipline, online training offers flexibility and scale. Hybrid approaches—recorded videos with real-time mentoring—are emerging as the most favored format.

Career Opportunities Post Power BI Certification

From being a Power BI Developer to becoming a Data Analyst, BI Consultant, or a Dashboard Architect, the list goes on. With a strong certification, even the door to freelancing and work-from-home positions all around the world opens.

Final Thoughts: Picking the Right Path for Your BI Career

The proper Power BI Certification Training Course in Bangalore can be a career spur. Assess your learning style, browse institute offerings, and consider where alumni work. The world of BI awaits—and Bangalore may be the perfect place to start.

#power bi #online training

0 notes

umarblog1 · 1 month ago

Text

Data Analyst Course in Noida: Online vs. Offline Learning – Which Is Better?

In today’s world, data is very important. Companies are using data to make smart decisions. Because of this, the job of a data analyst is in high demand. If you are someone who wants to become a data analyst, then learning the right skills is your first step. Many students in Noida are now choosing to take a Data Analyst course to build a good career.

But there is one big question: Should you learn online or offline? Both types of learning have their own advantages and disadvantages. In this article, we will help you understand the difference between online and offline Data Analyst courses. We will also help you decide which one is better for you.

Let’s explore both options in detail, with the help of Uncodemy, a trusted name in tech training.

What Is a Data Analyst Course?

Before we talk about online vs. offline, let’s understand what a Data Analyst course is.

A Data Analyst course teaches you how to:

Collect and clean data

Analyze and find patterns

Use tools like Excel, SQL, Power BI, Python, and Tableau

Present your results in charts and graphs

Help companies make better decisions using data

At Uncodemy, the Data Analyst course is designed for beginners as well as professionals. You do not need a coding background to start.

Online Data Analyst Course – What You Should Know

What Is It?

An online course is where you learn from home using a laptop or mobile. The classes are live or recorded, and you can study at your own pace. Uncodemy offers online live classes, real-time doubt clearing, and personal mentorship.

Benefits of Online Learning

Learn from Anywhere You don’t need to travel to a classroom. You can learn from your home, café, or even while traveling.

Flexible Timing You can choose your own study time. This is perfect if you are working or a college student.

Recorded Sessions Missed a class? No problem! You can watch the recorded video anytime.

One-on-One Mentorship Platforms like Uncodemy offer personal mentorship and live doubt-solving sessions online.

Access to Resources You get notes, practice questions, and project files online. Everything is one click away.

Saves Time and Money You don’t spend time or money on travel, and the course fees are often lower than offline classes.

Offline Data Analyst Course – What You Should Know

What Is It?

An offline course is where you go to a classroom and attend classes physically. You meet your trainer and classmates face-to-face.

Benefits of Offline Learning

Face-to-Face Interaction You can meet your teacher directly and ask questions on the spot.

Classroom Environment A physical class helps many students focus better without distractions.

Group Learning You meet other students and learn together. This improves teamwork and communication skills.

Hands-On Practice You work on computers in the classroom and get direct help when stuck.

Motivation and Routine Regular classes help build a routine, and being in a classroom can keep you motivated.

Online vs. Offline – Head-to-Head Comparison

FeatureOnline Learning (Uncodemy)Offline LearningFlexibilityHigh – Learn anytime, anywhereLow – Fixed timings and locationTravelNot neededRequiredInteractionVirtual (Zoom, Google Meet)Face-to-faceCostUsually more affordableSlightly higher due to classroom costsLearning ResourcesAvailable 24/7 onlineGiven during class or printedSupportChat, email, video calls, LMSDirect help in personClass RecordingAvailable (re-watch anytime)Not availableNetworkingOnline community, LinkedIn groupsDirect interaction with classmatesTime ManagementMore flexibleLess flexibleLearning SpeedLearn at your own paceMust match the class speed

Which One Should You Choose?

Choose Online If You:

Want to save travel time

Have a job or college and need flexible hours

Prefer learning at your own speed

Want to access global trainers from anywhere

Need budget-friendly options

Uncodemy’s online Data Analyst course is a great choice. It includes live training, industry projects, and placement assistance.

Choose Offline If You:

Prefer face-to-face interaction

Want a regular classroom environment

Need someone to guide you in person

Find it hard to focus at home

Uncodemy also has offline centers in Noida, where students can get personal attention and structured learning.

What Makes Uncodemy the Best Choice for Both Modes?

Whether you go online or offline, Uncodemy offers:

Certified Trainers with Industry Experience

Live Projects and Assignments

Interview Preparation

Placement Support

Internship Opportunities

Doubt Sessions and Career Mentorship

Students from all over India trust Uncodemy for their career growth.

Real Student Feedback – Online vs. Offline at Uncodemy

Online Learner (Priya – Working Professional)

“I chose Uncodemy’s online Data Analyst course because I work full-time. The live classes and recordings helped me learn after work hours. My mentor helped me with projects and resume building. I got placed within 3 months!”

Offline Learner (Rohit – College Graduate)

“I joined the offline course in Noida. The trainer was very helpful, and the hands-on practice in class cleared all my doubts. I enjoyed learning with other students. Now I’m working in a top IT company as a data analyst.”

Online Learning: Common Myths vs. Reality

MythRealityNo personal touchYou get one-on-one mentorship at UncodemyNo disciplineTimetable and reminders help you stay focusedLow qualityUncodemy’s quality is the same in both modesCan’t ask doubts in real timeLive doubt sessions are available

Offline Learning: Common Concerns

ConcernHow Uncodemy Solves ItLong travel timeClasses are scheduled with flexible slotsHigher feeValue-added training and placement supportFixed scheduleEarly morning or weekend batches availableLimited trainersAll instructors are industry experts

Final Verdict – Online vs. Offline: Which Is Better?

There is no one-size-fits-all answer. The best mode of learning depends on your goals, lifestyle, and learning style.

If you are self-motivated and want flexible learning, then online is a great option. If you prefer structure, routine, and in-person learning, then offline is better.

Both options at Uncodemy are high-quality and designed to give you the skills needed to become a successful data analyst.

Conclusion

Becoming a data analyst can open the door to exciting and high-paying jobs. Whether you choose online or offline, what matters most is taking action and staying consistent.

With Uncodemy’s Data analyst course in Noida, you don’t need to worry about quality, support, or placement. Choose the mode that suits your lifestyle, and Uncodemy will help you reach your career goals.

0 notes

shreja · 2 months ago

Text

Learn SQL with Global Teq

Master SQL – The Language of Data

Are you ready to learn the language that powers every modern business?

Global Teq's career-focused SQL course takes you from zero to work-ready—in case you're starting a tech career or need to upskill for your current role.

✅ Why Learn SQL?

📊 In-demand Skill: Used in data analysis, web development, software engineering, and business intelligence.

🏢 Used by Top Companies: SQL is the foundation behind tools like Power BI, Tableau, MySQL, and Microsoft Fabric.

💼 Career Boost: Data-related roles are growing fast—and SQL is often a core requirement.

🔍 What You’ll Learn in Our Course

SQL basics: SELECT, INSERT, UPDATE, DELETE

Filtering and sorting data

Table relationships and JOIN operations

Aggregation, GROUP BY, HAVING

Writing subqueries and nested queries

Real-world scenarios with hands-on practice

📦Course Features

🕒Expert video instruction 24/7

💻Live database-based hands-on practice

📞Instructor and mentor support

🧠Ideal for those with no prior coding experience

🎓Who Should Join?

Aspiring Data Analysts and Data Engineers

IT professionals looking to reskill

Business users looking to learn about data

Students looking to join the tech industry

🚀Why Global Teq?

Global Teq is a trusted global training organization in IT and data. Our training is designed by experts and designed to make you job-ready with our skills.

🔗Learn Today

Join the thousands of learners who have elevated their careers with our SQL course.

👉Enroll Now – Try the First Module Free!

https://www.global-teq.com/

0 notes

snaxsingh · 2 months ago

Text

Gain a Competitive Edge with Practical Data Science Training

Today, it is impossible to rely only on an employer's theoretical background to be versatile, just data analysis and They of data science. Employers expect individuals who can go straight from contributing to an organization, tackle 'communications challenges', and devise practical solutions. This is where hands-on training becomes invaluable, especially for those aiming to kickstart their career with a data science certification service in Pune.

This blog offers practical tips and industry-oriented advice to academically, professionally, or intrinsically challenged individuals about making a jumpstart towards their career and workforce team to get hired.

Why Hands-On Training Matters More Than Ever

The IT products and technologies market is continuously developing and expanding rapidly. Employers no longer look for degree certificates; nothing can be more fruitful than ditching the paperwork and entering the field.

This is why practical training should always be given prominence:

1. Learn by Doing

Although theory formation is essential to developing one's knowledge, real learning begins when one tries to solve a problem using the theory that has been created.

For instance, you may learn about logistic regression and how it works on the conceptual level. Still, when you apply the concept to customer churn data to make predictions on which clients are likely to churn and equally possible not to churn, among other things, it becomes astounding.

Rather than only encountering their names, it gives confidence to interact with procedures like Python, SQL, Tableau, and Jupyter notebooks.

2. Real-World Projects to Build Your Portfolio

Another advantage related to the abovementioned advantage is that hands-on data science training is carried out in Pune, focusing on real datasets and projects.

Work such as predicting the demand for a chain of stores, identifying fraudulent activities in banking or financial organisations, or deciding better routes for delivery trucks for a food delivery application is highly valuable when it comes to resumes.

All these projects prove your capability to analyse business-related issues using data.

3. Develop a Problem-Solving Mindset

Always, hands-on training requires gathering the training dataset and learning data science concepts such as adapting assumptions, array cleansing, selecting the ideal model, and prototyping.

Example: While working on an e-commerce recommendation system, you might realize missing data or unbalanced classes in your dataset. Your ability to spot and fix such issues makes you valuable to employers.

What Makes a Good Data Science Certification in Pune?

Choosing the right learning path is crucial. With the city growing as a tech and education hub, there are plenty of opportunities to find the right fit.

Here's what to look for:

Project-Based Curriculum

Make sure the data science course in Pune offers real-world projects instead of just video lectures. Interactive learning helps retain concepts and makes your training more job-oriented.

Exposure to Industry Tools

Tools like Python, Pandas, Scikit-learn, Power BI, and cloud platforms should be a core part of your training. These are the technologies that companies in Pune and beyond use.

Guidance from Experts

The best learning happens when experienced professionals mentor you. They clarify concepts and share practical tips from their work experience.

Real-Life Example: From Fresh Graduate to Data Analyst

Meet Meenal, a commerce graduate based in Pune. Despite having no background in tech, she had a passion for numbers and wanted to enter the data field. She enrolled in a hands-on data science certification in Pune, where she learned Python, data cleaning, and visualization.

The capstone project, where she analysed customer purchasing patterns for a supermarket chain, set her apart. This project helped her crack interviews confidently, and today, she works as a junior data analyst at a leading Pune-based firm.

Her success wasn't based on a degree; her practical skills and project experience made her job-ready.

How Data Science Training in Pune Aligns with Job Market Demands

Pune is no longer just an education city—it's now a booming IT and analytics hub. From startups to large enterprises, companies here are actively hiring data professionals.

A data science course in Pune prepares you for a variety of roles, including:

Data Analyst

Business Intelligence Developer

Machine Learning Engineer

Data Engineer

AI Specialist

And what's fueling this demand?

Digital transformation is occurring in industries like finance, e-commerce, logistics, and healthcare.

Increased use of data in decision-making and business forecasting.

Due to a rich talent pool and infrastructure, startups and MNCS are setting up operations in Pune.

What You'll Gain from a Data Science Certification in Pune

Let's break down some of the most valuable takeaways from a quality certification program:

Job-Ready Portfolio

With 4–6 industry-grade projects, you'll have a solid portfolio to impress employers.

Soft Skills & Interview Prep

Many programs now focus on resume building, mock interviews, and soft skills, which matter just as much as technical expertise.

Networking Opportunities

Collaborating with peers and mentors opens doors for job referrals and real-world insights. Being part of Pune's tech network can fast-track your job hunt.

Tips to Maximise Your Hands-On Learning

Start small, but be consistent – Tackle mini-projects weekly on platforms like Kaggle.

Join local meetups or webinars – Pune has a vibrant data community, both online and offline.

Document everything – Maintain a GitHub portfolio to showcase your work.

Keep learning – Data science evolves constantly; stay updated with new tools and techniques.

Final Thoughts: The Job-Ready Edge

The key to breaking into data science isn't memorising formulas—it's showing that you can solve real problems with data. Hands-on experience gives you that edge. With the growing demand for skilled professionals, taking a data science certification in Pune is not just an academic step—it's a career accelerator.

If you want to be employable from day one, practical data science training in Pune is your gateway to thriving in this competitive field. Equip yourself with tools, build your portfolio, and let your skills speak louder than your resume.

Your journey into data science starts now. Make it hands-on, real, and count.

#data science #data scientist

1 note · View note

pallaviicert · 3 months ago

Text

How to be an AI consultant in 2025

Artificial Intelligence (AI) is becoming a necessary part of companies worldwide. Companies of any size are implementing AI to optimize operations, enhance customer experience, and gain competitive edge. Demand for AI consultants is skyrocketing as a consequence. If you want to be an AI consultant in 2025, this guide will lead you through the necessary steps to set yourself up in this high-paying industry.

Appreciating the Role of an AI Consultant An AI consultant facilitates the incorporation of AI technologies into an organization's business processes. The job can include: •Assessing business needs and deciding on AI-based solutions. •Implementing machine learning models and AI tools. •AI adoption and ethical considerations training teams. •Executing AI-based projects according to business objectives. •Monitoring AI implementation plans and tracking effects. Since AI is evolving at a rapid rate, AI consultants must regularly update their skills and knowledge to stay in the competition.

Step 1: Establish a Solid Academic Base You would need to be very knowledgeable in AI, data science, and business to be an AI consultant. The following are the ways through which you can increase your awareness:

Formal Education • Bachelor's Degree: Bachelor of Computer Science, Data Science, Artificial Intelligence, or a related field is preferred. • Master's Degree (Optional): Having a Master's in AI, Business Analytics, or MBA with technical specialisation would be an added advantage to your qualification.

Step 2: Acquire Technical Skills Practical technical knowledge is needed in AI consulting. The most critical skills are: Computer Languages

Python: Used most to develop AI.

R: Statistical analysis and data visualization.

SQL: To communicate with the database.

Java and C++: Only occasionally used for AI applications.

Machine Learning and Deep Learning

• Scikit-learn, TensorFlow, PyTorch: Main software to create AI models.

• Natural Language Processing (NLP): Explore the relationship between human language and artificial intelligence.

• Computer Vision: AI learning of image and video processing.

Data Science and Analytics • Data Wrangling & Cleaning: Ability to pre-process raw data for AI models. - Big Data Tools: Hadoop, Spark, and Apache Kafka. • Experience in using tools such as Tableau, Power BI, and Matplotlib. Cloud Computing and Artificial Intelligence Platforms AI-driven applications are most frequently implemented in cloud environments.

Discover: • AWS AI and ML Services • Google Cloud AI • Microsoft Azure AI

Step 3: Gain Practical Experience While book knowledge is important, hands-on knowledge is invaluable. Here is what you can do to build your expertise: Working on AI Projects Start with tiny AI projects such as:

Developing a chatbot using Python.

Building a recommendation system.

Incorporating a model for fraud detection.

Applying AI to drive analytics automation.

Open-Source Contributions Join open-source AI projects on websites like GitHub. This will enhance your portfolio and make you authoritative in the eyes of the AI community.

Step 4: Economy Your Business and Consulting Experience

Technology is just part of the equation for AI consulting, you need to understand business strategy and how to articulate the advantages of AI as well. This is how:

Understanding of Business

Discover the impact of artificial intelligence on various fields of activity such as: retail, healthcare or banking.

Understand business intelligence and digital transformation of business.

Keep abreast of AI laws and ethics.

Management of Time and Timing

Understand AI assessments for organisations.

Improve your public speaking and your appearance.

Mastering stakeholder management and Negotiation skills.

Write AI strategy briefings in a way that the non-technical executives understand.

Creating a Portfolio and Personal Brand.

Step 5: Establish a Solid Portfolio & Personal Brand

Construct an AI Portfolio

Demonstrate your skill by constructing a portfolio with:

AI case studies and projects.

Research articles or blog posts on AI trends.

GitHub repositories and open-source contributions.

Build an Online Platform • Start a YouTube channel or blog to share AI knowledge. • Post blogs on LinkedIn or Medium. • Contribute to forums like Kaggle, AI Stack Exchange, and GitHub forums.

Step 6: Network & Get Clients You can get a network to obtain your AI consulting work. Here's how to do it: • Visit conferences such as NeurIPS, AI Summit, and Google AI conferences. • Join LinkedIn groups and subreddits on AI. • Engage with industry professionals through webinars and networking sessions. • Network with startups and firms looking for AI services.

Step 7: Offer AI Consulting Services You can now build your consulting foundation. Consider the following: • Freelancing: Work as an independent AI consultant. • Join a Consulting Company: Firms like Deloitte, Accenture, and McKinsey hire AI consultants. • Start Your Own AI Consultancy: If you're business-minded, start your own AI consulting business.

Step 8: Stay Current & Continuously Learn AI develops at light speed, so learn again and again. Watch out for:

AI research papers on Arxiv and Google Scholar.

AI newsletters such as Towards Data Science, OpenAI news.

Podcasts such as "AI Alignment" and "The TWIML AI Podcast".

AI leaders like Andrew Ng, Yann LeCun, and Fei-Fei Li.

Conclusion

By 2025, you must possess technical, business, and strategic communication skills in order to become an AI consultant. If you receive proper education, gain technical and business skills, possess a quality portfolio, and strategically network, then you can become a successful AI consultant. The key to success is continuous learning and adapting to the evolving AI landscape. If you’re passionate about AI and committed to staying ahead of trends, the opportunities in AI consulting are limitless!

Website: https://www.icertglobal.com/

#AI #Training #Course

0 notes

techscaler-solutions · 6 months ago

Text

Master Data Like a Pro: Discover the Best Online SQL BI Training Course

In the digital age, data drives every decision. From small startups to global corporations, businesses rely on insights drawn from their data. That’s why SQL (Structured Query Language) and Business Intelligence (BI) are among the most sought-after skills in the tech industry today.

Learning SQL and BI empowers professionals to analyze data, create insightful dashboards, and support decision-making. Whether you’re a beginner or an experienced professional looking to upskill, the best online SQL BI training course can pave the way for your career growth in the ever-expanding data landscape.

What Makes a Training Course Stand Out?

Not all SQL BI courses are created equal. A great course doesn’t just teach you concepts—it ensures you can apply them in real-world scenarios. The best online SQL BI training course will combine theoretical knowledge with hands-on projects, interactive assignments, and real-life case studies.

Moreover, accessibility is key. Look for a course that offers flexible schedules, downloadable resources, and on-demand videos. This ensures you can learn at your own pace while juggling other commitments. A good course should also provide industry-recognized certifications to add credibility to your newly acquired skills.

Benefits of Enrolling in the Best Online SQL BI Training Course

First and foremost, an online SQL BI training course offers flexibility. Whether you’re a full-time professional or a student, you can learn anytime, anywhere. This convenience makes it easier for learners to stay consistent and complete the course.

Additionally, these courses often include expert-led sessions and peer interactions, helping you understand complex concepts through collaborative learning. The best online SQL BI training course also gives you access to up-to-date tools and techniques, ensuring you stay ahead in a competitive field.

Top Features to Look for in an Online SQL BI Course

When searching for the best online SQL BI training course, keep an eye out for these features:

Comprehensive Curriculum: Ensure the course covers everything from SQL basics to advanced BI tools like Power BI, Tableau, and SSRS.

Hands-On Projects: Practical assignments are essential for mastering data manipulation, visualization, and analysis.

Expert Instructors: Learn from industry veterans who can share insights and tips that go beyond textbooks.

Support and Community: Access to discussion forums and Q&A sessions can significantly enhance your learning experience.

Choosing a course that ticks all these boxes ensures you get the most out of your learning journey.

How to Get Started on Your Learning Journey

Ready to take the plunge? Begin by identifying your goals. Are you looking to boost your career prospects, start a new job, or simply understand data better? Once you’re clear on your objectives, enroll in the best online SQL BI training course that aligns with your aspirations.

Don’t forget to dedicate time each week to learning. Stay consistent, complete all assignments, and participate in discussions to make the most of the course. By the end, you’ll have the confidence and skills to transform raw data into actionable insights—a skill every organization values.

Conclusion: Unlock Your Potential with the Right Training

Investing in the best online SQL BI training course is a step towards becoming a data expert. With flexible schedules, expert guidance, and practical learning, you’ll be equipped to tackle data challenges and elevate your career. Don’t wait—start your journey today!

0 notes

manoharnaresh-it · 7 months ago

Text

𝗨𝗻𝗹𝗲𝗮𝘀𝗵 𝘁𝗵𝗲 𝗣𝗼𝘄𝗲𝗿 𝗼𝗳 𝗗𝗮𝘁𝗮 𝘄𝗶𝘁𝗵 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗢𝗻𝗹𝗶𝗻𝗲 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗮𝘁 𝗡𝗮𝗿𝗲𝘀𝗵-𝗜𝗧!

Enroll now : https://nareshit.com/courses/power-bi-online-training

Course Overview

Naresh IT offers top-notch Power BI training, both online and in the classroom, aimed at equipping participants with an in-depth grasp of Microsoft Power BI, a premier business intelligence and data visualization platform. Our course delves into crucial facets of data analysis, visualization, and reporting utilizing Power BI. Through hands-on sessions, students will master the creation of dynamic dashboards, data source connectivity, and the extraction of actionable insights. Join Naresh IT for unrivaled expertise in Power BI.

Learn software skills with real experts, either in live classes with videos or without videos, whichever suits you best.

Description

The Power BI course begins with an introduction to business intelligence and the role of Power BI in transforming raw data into meaningful insights. Participants will learn about the Power BI ecosystem, including Power BI Desktop, Power BI Service, and Power BI Mobile. The course covers topics such as data loading, data transformation, creating visualizations, and sharing reports. Practical examples, hands-on projects, and real-world scenarios will be used to reinforce theoretical concepts.

Course Objectives

The primary objectives of the Power BI course are as follows:

Introduction to Business Intelligence and Power BI: Provide an overview of business intelligence concepts and the features of Power BI.

Power BI Ecosystem: Understand the components of the Power BI ecosystem, including Power BI Desktop, Service, and Mobile.

Data Loading and Transformation: Learn the process of loading data into Power BI and transforming it for analysis and visualization.

Data Modeling: Gain skills in creating data models within Power BI to establish relationships and hierarchies.

Creating Visualizations: Explore the various visualization options in Power BI and create interactive and informative reports and dashboards.

Advanced Analytics: Understand how to leverage advanced analytics features in Power BI, including DAX (Data Analysis Expressions) for calculations.

Power BI Service: Learn about the cloud-based service for sharing, collaborating, and publishing Power BI reports.

Data Connectivity: Explore the options for connecting Power BI to various data sources, including databases, cloud services, and Excel.

Sharing and Collaboration: Understand how to share Power BI reports with others, collaborate on datasets, and use workspaces.

Security and Compliance: Explore security measures and compliance considerations when working with sensitive data in Power BI.

Prerequisites

Basic understanding of data analysis concepts.

Familiarity with Microsoft Excel and its functions.

Knowledge of relational databases and SQL.

Understanding of data visualization principles.

Awareness of business intelligence (BI) concepts and tools.

Experience with basic data modeling and transformation techniques.

Course Curriculum

SQL (Structured Query Language)

What is SQL?

What is Database?

Difference between SQL and Database

Types of SQL Commands

Relationships in SQL

Comments in SQL

Alias in SQL

Database Commands

Datatypes in SQL

Table Commands

Constraints in SQL

Operators in SQL

Clauses in SQL

Functions in SQL

JOINS

Set operators

Sub Queries

Views

Synonyms

Case Statements

Window Functions

Introduction to Power BI

Power BI Introduction

Power BI Desktop (Power Query, Power Pivot, Power View, Data Modelling)

Power BI Service

Flow of Work in Power BI

Power BI Architecture

Power BI Desktop Installation

Installation through Microsoft Store

Download and Installation of Power BI Desktop

Power Query Editor / Power Query

Overview of Power Query Editor

Introduction of Power Query

UI of Power Query Editor

How to Open Power Query Editor

File Tab

Inbuilt Column Transformations

Inbuilt Row Transformations

Query Options

Home Tab Options

Transform Tab Options

Add Column Tab

Combine Queries (Merge and Append Queries)

View Tab Options

Tools Tab Options

Help Tab Options

Filters in Power Query

Data Modelling / Model View

What is InMemory Columnar database and advantages

What is Traditional database

Difference between InMemory Columnar database and Traditional database

xVelocity In-memory Analytics Engine (Vertipaq Engine)

Data Connectivity modes in Power BI

What is Data Modelling?

What are a Relationships?

Types of Relationships/Cardinalities

One-to-One, One-to-many, Many-to-One, Many-to-Many

Why do we need a Relationship?

How to create a relationship in Power BI

Edit existing relationship

Delete relationship

AutoDetect Relationship

Make Relationship Active or Inactive

Cross filter direction (Single, Both)

Assume Referential Integrity

Apply Security Filter in Both Directions

Dimension Column, Fact Column.

Dimension table, Fact Table

What is Schema?

Types of Schemas and Advantages

Power View / Report View

Introduction to Power View

What and why Visualizations?

UI of Report View/Power View

Difference between Numeric data, Categorical data, Series of data

Difference between Quantitative data and Qualitative data

Categorical data Visuals

Numeric and Series of Data

Tabular Data

Geographical Data

KPI Data

Filtering data

Filters in Power View

Drill Reports

Visual Interactions

Grouping

Sorting

Bookmarks in Power BI

Selection Pane in Power BI

Buttons in Power BI

Tooltips

Power BI Service

Power BI Architecture

How to Sign into Power BI Service account

Power Bi Licences (Pro & Premium Licences)

Team Collaboration in Power BI using Workspace

Sharing Power BI Content using Basic Sharing, Content Packs and Apps

Refreshing the Data Source

Deployment Pipelines

Row Level Security (RLS)

#PowerBI #PowerBIDesktop #DataVisualization #DataAnalytics #BusinessIntelligence #PowerBIAI #DataStorytelling

0 notes

lo4354 · 8 months ago

Text

To do Sunday

Remind yourself if you get stressed the only person's expectations you have to meet are YOUR OWN!

Watch the 3 hr SQL video and take notes on how to write queries. In between use sql bolt to try it out.

If you have time today - update the resume based on the ATS feedback. Next Week Game Plan: Put together a SQL query to pull data of containers leaving a place with nothing added, type nonchem or chem, cross check with items with same timestamp of divert leaving with same attribute. Attempt to do it based on your knowledge.. if you cant just show what you got and dont worrry - YOU GOT THIS!

Continue applying to 3 jobs daily. Make sure to run an AI check on the resume to make sure the buzz words matches. Yoga starts Oct 24 - do not skip any of these remember self care is priority! If you can master the SQL in next 2 weeks, we will move on to the Power BI training, if that works aim to get the google cloud leader cert. Priority List: P1: Self care Yoga Hydration Eat food Sleep on time P2: Skill overlap between work and job search SQL and Power BI, SQL is higher now. If you can use this you can use it for job search and at work. P3: Regular work P4: Resume edits + Job Application & Networking

1 note · View note

umarblog1 · 2 months ago

Text

Common Mistakes Students Make During a Data Analyst Course in Noida

Becoming a data analyst is a great career choice today. Companies are hiring skilled data analysts to understand their data and make smart decisions. Many students join a data analyst course in Noida to start their journey in this field. But sometimes, students make mistakes during the course that can slow down their learning or reduce their chances of getting a good job.

At Uncodemy, we have helped hundreds of students become successful data analysts. Based on our experience, we have listed some common mistakes students make during a data analyst course and how to avoid them. Read carefully so that you can learn better and get the most from your training.

1. Not Practicing Enough

One of the biggest mistakes students make is not practicing what they learn. Data analysis is a skill that requires hands-on work. You can’t become good at it by only watching videos or reading notes.

What You Should Do:

After every class, try to practice the concepts you learned.

Use platforms like Kaggle to work on real datasets.

Practice using Excel, SQL, Python, and other tools regularly.

Set a goal to spend at least 1–2 hours every day on practice.

2. Skipping the Basics

Many students want to learn advanced things quickly. They ignore the basics of Excel, statistics, or programming. This can be a big problem later because all advanced topics are built on the basics.

What You Should Do:

Take your time to understand basic Excel functions like VLOOKUP, Pivot Tables, etc.

Learn basic statistics: mean, median, mode, standard deviation, etc.

Start with simple Python or SQL commands before jumping into machine learning or big data.

3. Not Asking Questions

Some students feel shy or afraid to ask questions during the class. But if you don’t clear your doubts, they will keep piling up and confuse you more.

What You Should Do:

Don’t be afraid to ask questions. Your trainer is there to help.

If you feel uncomfortable asking in front of others, ask one-on-one after the class.

Join discussion forums or WhatsApp groups created by your training institute.

4. Focusing Only on Theory

A common mistake is spending too much time on theory and not enough on real-world projects. Companies don’t hire data analysts for their theory knowledge. They want someone who can solve real problems.

What You Should Do:

Work on multiple data projects like sales analysis, customer behavior, or survey data.

Add these projects to your resume or portfolio.

Uncodemy offers project-based learning—make sure you take full advantage of it.

5. Ignoring Soft Skills

Some students think only technical skills are important for a data analyst. But communication, teamwork, and presentation skills are also very important.

What You Should Do:

Practice explaining your analysis in simple words.

Create PowerPoint presentations to show your project findings.

Learn how to talk about your projects in interviews or meetings.

6. Not Learning Data Visualization

Data analysts must present their findings using charts, graphs, and dashboards. Some students skip learning tools like Power BI or Tableau, thinking they are not necessary. This is a big mistake.

What You Should Do:

Learn how to use Power BI or Tableau to make dashboards.

Practice making clear and beautiful visualizations.

Always include visual output in your projects.

7. Not Understanding the Business Side

Data analysis is not just about numbers. You must understand what the data means for the business. Students who only focus on the technical side may not solve the real problem.

What You Should Do:

Learn about different business functions: marketing, sales, HR, finance, etc.

When you work on a dataset, ask yourself: What problem are we trying to solve?

Talk to mentors or trainers about how businesses use data to grow.

8. Not Updating Resume or LinkedIn

You may become skilled, but if you don’t show it properly on your resume or LinkedIn, recruiters won’t notice you.

What You Should Do:

Update your resume after completing each project or module.

Add all certifications and tools you’ve learned.

Share your learning and projects on LinkedIn to build your presence.

9. Not Preparing for Interviews Early

Some students wait till the end of the course to start preparing for interviews. This is a mistake. Interview preparation takes time.

What You Should Do:

Start practicing common interview questions from the second month of your course.

Take mock interviews offered by Uncodemy.

Learn how to explain your projects confidently.

10. Not Choosing the Right Institute

Another mistake is choosing a training center that does not provide quality training, support, or placement help. This can waste your time and money.

What You Should Do:

Choose a trusted institute like Uncodemy that offers:

Experienced trainers

Hands-on projects

Interview and resume support

Placement assistance

Flexible timings (weekend or weekday batches)

11. Not Managing Time Properly

Many students, especially working professionals or college students, find it hard to balance their studies with other responsibilities. This leads to missed classes and incomplete assignments.

What You Should Do:

Make a weekly schedule for learning and stick to it.

Attend all live sessions or watch recordings if you miss them.

Complete small goals every day instead of piling work on weekends.

12. Not Joining a Learning Community

Learning alone can be hard and boring. Many students lose motivation because they don’t stay connected with others.

What You Should Do:

Join a study group or class group at Uncodemy.

Participate in hackathons or challenges.

Help others—you’ll learn better too!

13. Thinking Certification is Enough

Some students believe that just getting a certificate will get them a job. This is not true. Certificates are useful, but companies care more about your actual skills and experience.

What You Should Do:

Focus on building real projects and understanding the tools deeply.

Make a strong portfolio.

Practice solving business problems using data.

14. Not Reviewing Mistakes

Everyone makes mistakes while learning. But some students don’t take the time to review them and learn from them.

What You Should Do:

After every assignment or test, check where you made mistakes.

Ask your trainer to explain the right solution.

Keep a notebook to write down your weak areas and improve on them.

15. Trying to Learn Everything at Once

Some students try to learn too many tools and topics at the same time. This leads to confusion and poor understanding.

What You Should Do:

Follow a structured learning path, like the one offered at Uncodemy.

Master one tool at a time—first Excel, then SQL, then Python, and so on.

Focus on quality, not quantity.

Final Thoughts

A career in data analytics can change your life—but only if you take your training seriously and avoid the mistakes many students make. At Uncodemy, we guide our students step-by-step so they can become skilled, confident, and job-ready.

Remember, learning data analysis is a journey. Stay consistent, be curious, and keep practicing. Avoid the mistakes shared above, and you’ll be well on your way to a successful future.

If you’re looking for the best Data analyst course in Noida, Uncodemy is here to help you every step of the way. Contact us today to know more or join a free demo class.

0 notes

samiinfotech1 · 8 months ago

Text

Power BI Courses in Seawoods: Unlocking the Power of Data Analytics

In today's data-driven world, organizations across industries are leveraging data analytics to make informed decisions, optimize operations, and gain a competitive edge. Microsoft Power BI has emerged as one of the most popular tools for business intelligence and data visualization, helping professionals turn raw data into actionable insights. As a result, the demand for Power BI skills is on the rise, and many individuals are seeking opportunities to learn and master this tool. If you’re in Seawoods and interested in power bi courses seawoods, there are various options available for high-quality training.

Why Learn Power BI?

Power BI is a user-friendly yet powerful tool that allows users to create interactive dashboards, reports, and data visualizations. Its ability to connect to a wide variety of data sources, including Excel, databases, and cloud-based platforms, makes it an essential tool for analysts, business owners, and data scientists alike. With businesses increasingly relying on data analytics, acquiring Power BI skills can significantly boost your career opportunities.

Here are a few reasons why Power BI training is essential:

Data Visualization: Power BI helps present data in easy-to-understand formats through dynamic graphs and charts.

Data Connectivity: It connects to various data sources, facilitating seamless data analysis across multiple platforms.

User-Friendly: With an intuitive interface, Power BI is accessible for both beginners and advanced users.

Business Decision Making: The ability to quickly analyze data and create insightful reports supports better business decisions.

Power BI Courses in Seawoods

Seawoods, a bustling locality in Navi Mumbai, has seen a surge in educational and training centers offering courses in various disciplines, including Power BI. Whether you are a working professional seeking to upgrade your skills or a student aspiring to enter the data analytics field, you can find a variety of Power BI training options tailored to different needs.

Classroom Training

For those who prefer face-to-face interaction with instructors, many institutes in and around Seawoods offer classroom-based Power BI courses. These courses are typically structured to take students from the basics of Power BI to more advanced techniques, such as DAX (Data Analysis Expressions) and data modeling. Classroom training allows for real-time queries, hands-on exercises, and peer interaction, making it an excellent choice for learners who thrive in a traditional educational environment.

Online Courses

In recent years, online learning platforms have become increasingly popular. Many institutes in Seawoods now offer flexible online Power BI courses that allow students to learn at their own pace. These online courses often include recorded video lectures, live sessions, interactive quizzes, and downloadable resources. Online learning offers flexibility for those with busy schedules and provides the option to revisit material for better understanding.

Corporate Training

For businesses in Seawoods, corporate Power BI training programs are available. These are typically customized to the needs of the organization and focus on the specific ways Power BI can be integrated into a company's workflow. These corporate training sessions can be conducted on-site or virtually, and they often focus on team-based projects to apply Power BI in a practical business setting.

Course Content and Structure

While the specific content of Power BI courses may vary from one institute to another, most courses cover the following key areas:

Introduction to Power BI: Understanding the basics of Power BI, its components, and interface.

Data Connections: Learning how to connect Power BI to various data sources like Excel, SQL, and cloud services.

Data Transformation: Using Power Query Editor to clean and transform data before analysis.

Data Modeling: Building relationships between data tables and creating efficient data models.

Data Visualization: Creating interactive dashboards and reports using visuals like charts, graphs, and maps.

DAX Formulas: Learning Data Analysis Expressions (DAX) for advanced calculations and data manipulation.

Publishing and Sharing: Understanding how to publish reports to Power BI Service and collaborate with teams.

Choosing the Right Course

When selecting a power bi courses trombay, consider factors such as the course duration, the experience of the instructors, and the hands-on practice opportunities. Also, ensure that the course covers both the foundational aspects of Power BI and the advanced skills required for professional use. Whether you opt for classroom, online, or corporate training, the key is to choose a course that aligns with your learning style and career goals.

With businesses increasingly relying on data to drive their operations, Power BI has become a critical skill for professionals in various industries. Whether you're looking to start a career in data analytics or enhance your current role, learning Power BI can open up new opportunities. In Seawoods, there are several training options available, from classroom courses to flexible online learning, making it easier than ever to gain proficiency in this powerful tool. Investing in a Power BI course can be the first step towards mastering data analytics and making smarter, data-driven decisions.

0 notes

govindhtech · 8 months ago

Text

Boost AI Production With Data Agents And BigQuery Platform

Data accessibility can hinder AI adoption since so much data is unstructured and unmanaged. Data should be accessible, actionable, and revolutionary for businesses. A data cloud based on open standards, that connects data to AI in real-time, and conversational data agents that stretch the limits of conventional AI are available today to help you do this.

An open real-time data ecosystem

Google Cloud announced intentions to combine BigQuery into a single data and AI use case platform earlier this year, including all data formats, numerous engines, governance, ML, and business intelligence. It also announces a managed Apache Iceberg experience for open-format customers. It adds document, audio, image, and video data processing to simplify multimodal data preparation.

Volkswagen bases AI models on car owner’s manuals, customer FAQs, help center articles, and official Volkswagen YouTube videos using BigQuery.

New managed services for Flink and Kafka enable customers to ingest, set up, tune, scale, monitor, and upgrade real-time applications. Data engineers can construct and execute data pipelines manually, via API, or on a schedule using BigQuery workflow previews.

Customers may now activate insights in real time using BigQuery continuous queries, another major addition. In the past, “real-time” meant examining minutes or hours old data. However, data ingestion and analysis are changing rapidly. Data, consumer engagement, decision-making, and AI-driven automation have substantially lowered the acceptable latency for decision-making. The demand for insights to activation must be smooth and take seconds, not minutes or hours. It has added real-time data sharing to the Analytics Hub data marketplace in preview.

Google Cloud launches BigQuery pipe syntax to enable customers manage, analyze, and gain value from log data. Data teams can simplify data conversions with SQL intended for semi-structured log data.

Connect all data to AI

BigQuery clients may produce and search embeddings at scale for semantic nearest-neighbor search, entity resolution, semantic search, similarity detection, RAG, and recommendations. Vertex AI integration makes integrating text, photos, video, multimodal data, and structured data easy. BigQuery integration with LangChain simplifies data pre-processing, embedding creation and storage, and vector search, now generally available.

It previews ScaNN searches for large queries to improve vector search. Google Search and YouTube use this technology. The ScaNN index supports over one billion vectors and provides top-notch query performance, enabling high-scale workloads for every enterprise.

It is also simplifying Python API data processing with BigQuery DataFrames. Synthetic data can replace ML model training and system testing. It teams with Gretel AI to generate synthetic data in BigQuery to expedite AI experiments. This data will closely resemble your actual data but won’t contain critical information.

Finer governance and data integration

Tens of thousands of companies fuel their data clouds with BigQuery and AI. However, in the data-driven AI era, enterprises must manage more data kinds and more tasks.

BigQuery’s serverless design helps Box process hundreds of thousands of events per second and manage petabyte-scale storage for billions of files and millions of users. Finer access control in BigQuery helps them locate, classify, and secure sensitive data fields.

Data management and governance become important with greater data-access and AI use cases. It unveils BigQuery’s unified catalog, which automatically harvests, ingests, and indexes information from data sources, AI models, and BI assets to help you discover your data and AI assets. BigQuery catalog semantic search in preview lets you find and query all those data assets, regardless of kind or location. Users may now ask natural language questions and BigQuery understands their purpose to retrieve the most relevant results and make it easier to locate what they need.

It enables more third-party data sources for your use cases and workflows. Equifax recently expanded its cooperation with Google Cloud to securely offer anonymized, differentiated loan, credit, and commercial marketing data using BigQuery.

Equifax believes more data leads to smarter decisions. By providing distinctive data on Google Cloud, it enables its clients to make predictive and informed decisions faster and more agilely by meeting them on their preferred channel.

Its new BigQuery metastore makes data available to many execution engines. Multiple engines can execute on a single copy of data across structured and unstructured object tables next month in preview, offering a unified view for policy, performance, and workload orchestration.

Looker lets you use BigQuery’s new governance capabilities for BI. You can leverage catalog metadata from Looker instances to collect Looker dashboards, exploration, and dimensions without setting up, maintaining, or operating your own connector.

Finally, BigQuery has catastrophe recovery for business continuity. This provides failover and redundant compute resources with a SLA for business-critical workloads. Besides your data, it enables BigQuery analytics workload failover.

Gemini conversational data agents

Global organizations demand LLM-powered data agents to conduct internal and customer-facing tasks, drive data access, deliver unique insights, and motivate action. It is developing new conversational APIs to enable developers to create data agents for self-service data access and monetize their data to differentiate their offerings.

Conversational analytics

It used these APIs to create Looker’s Gemini conversational analytics experience. Combine with Looker’s enterprise-scale semantic layer business logic models. You can root AI with a single source of truth and uniform metrics across the enterprise. You may then use natural language to explore your data like Google Search.

LookML semantic data models let you build regulated metrics and semantic relationships between data models for your data agents. LookML models don’t only describe your data; you can query them to obtain it.

Data agents run on a dynamic data knowledge graph. BigQuery powers the dynamic knowledge graph, which connects data, actions, and relationships using usage patterns, metadata, historical trends, and more.

Last but not least, Gemini in BigQuery is now broadly accessible, assisting data teams with data migration, preparation, code assist, and insights. Your business and analyst teams can now talk with your data and get insights in seconds, fostering a data-driven culture. Ready-to-run queries and AI-assisted data preparation in BigQuery Studio allow natural language pipeline building and decrease guesswork.

Connect all your data to AI by migrating it to BigQuery with the data migration application. This product roadmap webcast covers BigQuery platform updates.

Read more on Govindhtech.com

#DataAgents #BigQuery #BigQuerypipesyntax #vectorsearch #BigQueryDataFrames #BigQueryanalytics #LookMLmodels #news #technews #technology #technologynews #technologytrends #govindhtech

0 notes

pallaviicert · 3 months ago

Text

How to be an AI consultant in 2025

Artificial Intelligence (AI) is becoming a necessary part of companies worldwide. Companies of any size are implementing AI to optimize operations, enhance customer experience, and gain competitive edge. Demand for AI consultants is skyrocketing as a consequence. If you want to be an AI consultant in 2025, this guide will lead you through the necessary steps to set yourself up in this high-paying industry.

Appreciating the Role of an AI Consultant An AI consultant facilitates the incorporation of AI technologies into an organization's business processes. The job can include: •Assessing business needs and deciding on AI-based solutions. •Implementing machine learning models and AI tools. •AI adoption and ethical considerations training teams. •Executing AI-based projects according to business objectives. •Monitoring AI implementation plans and tracking effects. Since AI is evolving at a rapid rate, AI consultants must regularly update their skills and knowledge to stay in the competition.

Step 1: Establish a Solid Academic Base You would need to be very knowledgeable in AI, data science, and business to be an AI consultant. The following are the ways through which you can increase your awareness:

Formal Education • Bachelor's Degree: Bachelor of Computer Science, Data Science, Artificial Intelligence, or a related field is preferred. • Master's Degree (Optional): Having a Master's in AI, Business Analytics, or MBA with technical specialisation would be an added advantage to your qualification.

Step 2: Acquire Technical Skills Practical technical knowledge is needed in AI consulting. The most critical skills are: Computer Languages

Python: Used most to develop AI.

R: Statistical analysis and data visualization.

SQL: To communicate with the database.

Java and C++: Only occasionally used for AI applications.

Machine Learning and Deep Learning

• Scikit-learn, TensorFlow, PyTorch: Main software to create AI models.

• Natural Language Processing (NLP): Explore the relationship between human language and artificial intelligence.

• Computer Vision: AI learning of image and video processing.

Data Science and Analytics • Data Wrangling & Cleaning: Ability to pre-process raw data for AI models. - Big Data Tools: Hadoop, Spark, and Apache Kafka. • Experience in using tools such as Tableau, Power BI, and Matplotlib. Cloud Computing and Artificial Intelligence Platforms AI-driven applications are most frequently implemented in cloud environments.

Discover: • AWS AI and ML Services • Google Cloud AI • Microsoft Azure AI

Step 3: Gain Practical Experience While book knowledge is important, hands-on knowledge is invaluable. Here is what you can do to build your expertise: Working on AI Projects Start with tiny AI projects such as:

Developing a chatbot using Python.

Building a recommendation system.

Incorporating a model for fraud detection.

Applying AI to drive analytics automation.

Open-Source Contributions Join open-source AI projects on websites like GitHub. This will enhance your portfolio and make you authoritative in the eyes of the AI community.

Step 4: Economy Your Business and Consulting Experience

Technology is just part of the equation for AI consulting, you need to understand business strategy and how to articulate the advantages of AI as well. This is how:

Understanding of Business

Discover the impact of artificial intelligence on various fields of activity such as: retail, healthcare or banking.

Understand business intelligence and digital transformation of business.

Keep abreast of AI laws and ethics.

Management of Time and Timing

Understand AI assessments for organisations.

Improve your public speaking and your appearance.

Mastering stakeholder management and Negotiation skills.

Write AI strategy briefings in a way that the non-technical executives understand.

Creating a Portfolio and Personal Brand.

Step 5: Establish a Solid Portfolio & Personal Brand

Construct an AI Portfolio

Demonstrate your skill by constructing a portfolio with:

AI case studies and projects.

Research articles or blog posts on AI trends.

GitHub repositories and open-source contributions.

Build an Online Platform • Start a YouTube channel or blog to share AI knowledge. • Post blogs on LinkedIn or Medium. • Contribute to forums like Kaggle, AI Stack Exchange, and GitHub forums.

Step 6: Network & Get Clients You can get a network to obtain your AI consulting work. Here's how to do it: • Visit conferences such as NeurIPS, AI Summit, and Google AI conferences. • Join LinkedIn groups and subreddits on AI. • Engage with industry professionals through webinars and networking sessions. • Network with startups and firms looking for AI services.

Step 7: Offer AI Consulting Services You can now build your consulting foundation. Consider the following: • Freelancing: Work as an independent AI consultant. • Join a Consulting Company: Firms like Deloitte, Accenture, and McKinsey hire AI consultants. • Start Your Own AI Consultancy: If you're business-minded, start your own AI consulting business.

Step 8: Stay Current & Continuously Learn AI develops at light speed, so learn again and again. Watch out for:

AI research papers on Arxiv and Google Scholar.

AI newsletters such as Towards Data Science, OpenAI news.

Podcasts such as "AI Alignment" and "The TWIML AI Podcast".

AI leaders like Andrew Ng, Yann LeCun, and Fei-Fei Li.

Conclusion

By 2025, you must possess technical, business, and strategic communication skills in order to become an AI consultant. If you receive proper education, gain technical and business skills, possess a quality portfolio, and strategically network, then you can become a successful AI consultant. The key to success is continuous learning and adapting to the evolving AI landscape. If you’re passionate about AI and committed to staying ahead of trends, the opportunities in AI consulting are limitless!

Website: https://www.icertglobal.com/

0 notes

abiinnovate · 10 months ago

Text

What is data science?

Data science is an interdisciplinary field that involves using scientific methods, algorithms, processes, and systems to extract knowledge and insights from structured and unstructured data. It combines elements of statistics, computer science, domain expertise, and data engineering to analyze large volumes of data and derive actionable insights.

Key Components of Data Science:

Data Collection

Definition: Gathering data from various sources, which can include databases, APIs, web scraping, sensors, and more.

Types of Data:

Structured Data: Organized in tables (e.g., databases).

Unstructured Data: Includes text, images, videos, etc.

Data Cleaning and Preparation

Definition: Processing and transforming raw data into a clean format suitable for analysis. This step involves handling missing values, removing duplicates, and correcting errors.

Importance: Clean data is crucial for accurate analysis and model building.

Exploratory Data Analysis (EDA)

Definition: Analyzing the data to discover patterns, trends, and relationships. This involves statistical analysis, data visualization, and summary statistics.

Tools: Common tools for EDA include Python (with libraries like Pandas and Matplotlib), R, and Tableau.

Data Modeling

Definition: Building mathematical models to represent the underlying patterns in the data. This includes statistical models, machine learning models, and algorithms.

Types of Models:

Supervised Learning: Models that are trained on labeled data (e.g., classification, regression).

Unsupervised Learning: Models that find patterns in unlabeled data (e.g., clustering, dimensionality reduction).

Reinforcement Learning: Models that learn by interacting with an environment to maximize some notion of cumulative reward.

Model Evaluation and Tuning

Definition: Assessing the performance of models using metrics such as accuracy, precision, recall, F1 score, etc. Model tuning involves optimizing the model parameters to improve performance.

Cross-Validation: A technique used to assess how the results of a model will generalize to an independent dataset.

Data Visualization

Definition: Creating visual representations of data and model outputs to communicate insights clearly and effectively.

Tools: Matplotlib, Seaborn, D3.js, Power BI, and Tableau are commonly used for visualization.

Deployment and Monitoring

Definition: Implementing the model in a production environment where it can be used to make real-time decisions. Monitoring involves tracking the model's performance over time to ensure it remains accurate.

Tools: Cloud services like AWS, Azure, and tools like Docker and Kubernetes are used for deployment.

Ethics and Privacy

Consideration: Ensuring that data is used responsibly, respecting privacy, and avoiding biases in models. Data scientists must be aware of ethical considerations in data collection, analysis, and model deployment.

Applications of Data Science:

Business Intelligence: Optimizing operations, customer segmentation, and personalized marketing.

Healthcare: Predicting disease outbreaks, personalized medicine, and drug discovery.

Finance: Fraud detection, risk management, and algorithmic trading.

E-commerce: Recommendation systems, inventory management, and price optimization.

Social Media: Sentiment analysis, trend detection, and user behavior analysis.

Tools and Technologies in Data Science:

Programming Languages: Python, R, SQL.

Machine Learning Libraries: Scikit-learn, TensorFlow, PyTorch.

Big Data Tools: Hadoop, Spark.

Data Visualization: Matplotlib, Seaborn, Tableau, Power BI.

Databases: SQL, NoSQL (MongoDB), and cloud databases like Google BigQuery.

Conclusion

Data science is a powerful field that is transforming industries by enabling data-driven decision-making. With the explosion of data in today's world, the demand for skilled data scientists continues to grow, making it an exciting and impactful career path.

data science course in chennai

data science institute in chennai

data analytics in chennai

data analytics institute in chennai

#data analytics

0 notes

manoharnaresh-it · 7 months ago

Text

Integrating Power BI with Azure Synapse Analytics for real-time data insights-NareshIT