#Linkedin Python assessment answers

[educationtech]

Master Your Campus Placements: Resume, Interviews & Beyond

To ace campus placements successfully, engineering students need a comprehensive roadmap that covers everything from resume building to clearing HR rounds. Here is an ultimate, step-by-step guide to help you navigate the entire placement process effectively:

1. Understand the Campus Placement Process

Familiarize yourself with the typical stages: pre-placement talks, written tests (aptitude, technical), coding rounds, technical interviews, and HR interviews.

Research the companies visiting your campus, their job roles, required skills, and work culture to tailor your preparation accordingly.

2. Build a Strong and Tailored Resume

Create a concise, well-structured resume highlighting your academic achievements, projects, internships, certifications, and relevant skills.

Customize your resume for each company based on their job description and desired skill set.

Include measurable accomplishments and technical proficiencies to stand out.

3. Strengthen Core Technical Knowledge

Focus on your branch-specific core subjects and ensure a solid understanding of fundamentals and advanced topics.

Stay updated with the latest developments in your field to demonstrate awareness and enthusiasm.

4. Master Coding and Programming Skills

Learn and practice programming languages commonly used in your domain (e.g., C++, Java, Python).

Develop strong problem-solving skills by studying data structures and algorithms (DSA).

Regularly solve coding challenges on platforms and participate in contests to improve speed and accuracy.

5. Prepare for Aptitude and Logical Reasoning Tests

Practice quantitative aptitude, logical reasoning, and verbal ability questions regularly.

Use mock tests and previous years’ placement papers to familiarize yourself with question patterns and time management.

6. Participate in Mock Tests and Group Discussions

Take mock tests for aptitude, coding, and technical interviews to assess your preparation level.

Engage in group discussions to improve communication skills, confidence, and ability to think on your feet.

7. Develop Soft Skills and Communication Abilities

Work on your verbal and non-verbal communication, including clarity, confidence, and body language.

Practice answering behavioral questions and situational responses commonly asked in HR rounds.

Build teamwork and leadership skills through extracurricular activities or internships.

8. Prepare for Technical and HR Interviews

For technical interviews, revise key concepts, projects, and be ready to solve problems on the spot.

For HR interviews, prepare to discuss your resume, career goals, strengths, weaknesses, and why you want to join the company.

Research common HR questions and practice answers that reflect your personality and professionalism.

9. Network and Seek Guidance

Connect with seniors, alumni, and professionals on platforms like LinkedIn to gain insights and mentorship.

Attend workshops, seminars, and placement cell sessions to stay updated and receive expert advice.

10. Maintain Consistency and Stay Positive

Start your preparation early and maintain a disciplined study routine.

Manage stress through regular breaks, exercise, and a positive mindset.

Keep track of your progress and continuously refine your strategies based on feedback and mock test results.

By following this structured roadmap-from understanding the process, building a compelling resume, honing technical and soft skills, to mastering interview techniques-you can significantly enhance your chances of securing your dream job through campus placements through Best College of Engineering in Jaipur which is Arya College of Engineering & I.T. Consistency, preparation, and a proactive approach are key to standing out in the competitive placement landscape.

[aryacollegeofengineering]

Ultimate Roadmap to Ace Campus Placements: From Resume Building to HR Rounds

To ace campus placements successfully, engineering students need a comprehensive roadmap that covers everything from resume building to clearing HR rounds. Here is an ultimate, step-by-step guide to help you navigate the entire placement process effectively:

1. Understand the Campus Placement Process

Familiarize yourself with the typical stages: pre-placement talks, written tests (aptitude, technical), coding rounds, technical interviews, and HR interviews.

Research the companies visiting your campus, their job roles, required skills, and work culture to tailor your preparation accordingly.

2. Build a Strong and Tailored Resume

Create a concise, well-structured resume highlighting your academic achievements, projects, internships, certifications, and relevant skills.

Customize your resume for each company based on their job description and desired skill set.

Include measurable accomplishments and technical proficiencies to stand out.

3. Strengthen Core Technical Knowledge

Focus on your branch-specific core subjects and ensure a solid understanding of fundamentals and advanced topics.

Stay updated with the latest developments in your field to demonstrate awareness and enthusiasm.

4. Master Coding and Programming Skills

Learn and practice programming languages commonly used in your domain (e.g., C++, Java, Python).

Develop strong problem-solving skills by studying data structures and algorithms (DSA).

Regularly solve coding challenges on platforms and participate in contests to improve speed and accuracy.

5. Prepare for Aptitude and Logical Reasoning Tests

Practice quantitative aptitude, logical reasoning, and verbal ability questions regularly.

Use mock tests and previous years’ placement papers to familiarize yourself with question patterns and time management.

6. Participate in Mock Tests and Group Discussions

Take mock tests for aptitude, coding, and technical interviews to assess your preparation level.

Engage in group discussions to improve communication skills, confidence, and ability to think on your feet.

7. Develop Soft Skills and Communication Abilities

Work on your verbal and non-verbal communication, including clarity, confidence, and body language.

Practice answering behavioral questions and situational responses commonly asked in HR rounds.

Build teamwork and leadership skills through extracurricular activities or internships.

8. Prepare for Technical and HR Interviews

For technical interviews, revise key concepts, projects, and be ready to solve problems on the spot.

For HR interviews, prepare to discuss your resume, career goals, strengths, weaknesses, and why you want to join the company.

Research common HR questions and practice answers that reflect your personality and professionalism.

9. Network and Seek Guidance

Connect with seniors, alumni, and professionals on platforms like LinkedIn to gain insights and mentorship.

Attend workshops, seminars, and placement cell sessions to stay updated and receive expert advice.

10. Maintain Consistency and Stay Positive

Start your preparation early and maintain a disciplined study routine.

Manage stress through regular breaks, exercise, and a positive mindset.

Keep track of your progress and continuously refine your strategies based on feedback and mock test results.

By following this structured roadmap-from understanding the process, building a compelling resume, honing technical and soft skills, to mastering interview techniques-you can significantly enhance your chances of securing your dream job through campus placements through Best Engineering College in Jaipur which is Arya College of Engineering & I.T. Consistency, preparation, and a proactive approach are key to standing out in the competitive placement landscape.

Source: Click Here

[manoj1224]

What to Look for When Hiring a Software Development Provider

What to Look for When Hiring a Software Development Provider

Introduction

In today’s digital world, having the right software solutions can be the key to business success. Whether you're a startup looking to build an innovative app or an established company needing custom software, choosing the right software development provider is crucial. The wrong choice can lead to delays, budget overruns, and a product that doesn’t meet your expectations. But with so many options available—freelancers, development agencies, and offshore teams—how do you choose a software developer that fits your needs?

This guide will walk you through everything you should consider when hiring a software development company, from technical expertise to project management, ensuring you find the best software development services for your business.

1. Define Your Project Needs and Goals

Before you start looking for a software development agency, you need to have a clear understanding of your project. Ask yourself:

What problem does the software need to solve?

What features and functionalities are essential?

What is your budget and timeline?

Do you need ongoing maintenance and support?

Having clear answers to these questions will help you communicate your vision effectively and ensure that the software development company you hire can deliver what you need.

2. Evaluate Technical Expertise and Experience

Not all software development providers have the same level of expertise. When evaluating potential candidates, consider:

Technology Stack

Check if the company specializes in the technologies you need. For example:

Web development: React, Angular, Node.js

Mobile apps: Swift (iOS), Kotlin (Android), Flutter, React Native

Enterprise solutions: Java, .NET, Python

Cloud computing: AWS, Azure, Google Cloud

If your project requires AI, blockchain, or IoT, ensure the software development agency has relevant experience in those areas.

Industry Experience

A software development company with experience in your industry will understand your specific challenges. For example, a provider that has built healthcare applications will be familiar with compliance regulations like HIPAA, while a fintech software developer will know security protocols like PCI-DSS.

Portfolio and Case Studies

A reputable software development provider should have a strong portfolio showcasing their past projects. Look for:

Case studies that highlight challenges and solutions

Live apps or platforms they have developed

Testimonials from previous clients

3. Assess Communication and Project Management

Even the most skilled software development company can fail if communication is poor. Look for a team that:

Is responsive: Do they reply to emails and messages promptly?

Uses clear processes: Do they follow Agile, Scrum, or Kanban methodologies?

Provides regular updates: Will they offer weekly reports, sprint reviews, or demo sessions?

Has a dedicated project manager: A PM ensures smooth communication between you and the development team.

Red Flag: If a company is vague about deadlines, doesn’t provide clear deliverables, or takes days to respond, it may lead to project delays.

4. Check Client Reviews and Reputation

Online reviews can reveal a lot about a software development agency. Check platforms like:

Clutch and GoodFirms for verified client reviews

LinkedIn for testimonials from professionals

Google Reviews and Trustpilot for overall ratings

If possible, contact previous clients to get direct feedback about their experience with the company.

5. Consider Pricing and Engagement Models

Pricing structures can vary depending on the software development provider. Here are the most common engagement models:

Fixed Price

Best for small, well-defined projects

Clear scope, budget, and timeline from the start

Less flexibility for changes

Time & Material (T&M)

Pay for actual work done (hourly or daily rates)

More flexibility to modify requirements

Suitable for evolving projects

Dedicated Team

A full-time team assigned exclusively to your project

Best for long-term development needs

Allows deeper integration with your in-house team

Always compare pricing, but don’t choose a provider based solely on cost. A cheaper software development agency may cut corners, leading to higher expenses later.

6. Test Their Problem-Solving Abilities

Technical skills are essential, but a great software development provider also needs strong problem-solving abilities. During the hiring process, ask:

How do you handle unexpected challenges in a project?

Can you provide an example of a difficult technical problem you solved?

What strategies do you use to ensure code quality and scalability?

This helps gauge their ability to think critically and adapt to real-world situations.

7. Discuss Post-Launch Support and Maintenance

Software development doesn’t end at launch. Ongoing support ensures your software remains functional, secure, and up to date. Ask about:

Bug fixes and troubleshooting: Will they provide free fixes for a certain period?

Updates and enhancements: How do they handle software upgrades?

Support availability: Is there 24/7 support, or only during business hours?

A reliable software development company will offer a clear post-launch support plan.

8. Ensure They Follow Security and Compliance Standards

Security is critical, especially if your software handles sensitive data. Make sure the provider:

Uses secure coding practices

Follows GDPR, HIPAA, or other industry regulations

Implements encryption and authentication protocols

Conducts regular security audits

Ignoring security can lead to data breaches, legal issues, and reputational damage.

Conclusion

Hiring the right software development provider is a crucial decision that can impact your business for years to come. By defining your project needs, evaluating technical expertise, ensuring effective communication, and considering pricing and support models, you can find the best software development services for your needs.

[ineubytes11]

Data Analytics Made Easy: Learn, Analyze, Succeed

Introduction

In today's digital world, data is everywhere—generated from online transactions, social media interactions and commercial activities. Companies use data analysis to gain meaningful insights, adapt decisions and stick to the competing market. Whether you are a beginner or a professional in search of an APCIL, data analysis mastery can open doors for exciting career opportunities. Registration for the best data analytics course online will help you develop the skills required to collect, analyze and interpret the data effectively.

This article will find out how data analysis works, its real-world applications and how to start your journey in this field.

What is Data analytics?

Data analysis is the process of checking raw data to highlight the pattern, trends and insights that can make strategic decisions. It includes different techniques, including statistical analysis, future modeling and machine learning.

Industry companies using data analysis:

Understand customer behavior

Improve operational efficiency

Customize marketing strategies

Predictions for future trends

Increase the product development

By converting the data into actionable insights, the business can create informed alternatives that lead to better results.

Four types of data analysis

Descriptive analysis

These types of analyses answer this question: "What happened?" It includes historical data briefly to understand previous trends and performance.

Clinical analysis

This answers the question, "Why did this happen?" This is dug deep into the data to identify causes and conditions.

Future analysis

This involves using statistical models and machine learning to predict future results based on historical data.

Prescription analyzes

The most advanced type of analysis, prescription analysis, suggests the best course of action based on data-operated predictions.

Real-World Applications of Data Analytics

Trade and marketing

Companies use data analysis to track customer preferences, measure marketing campaign efficiency and adapt pricing strategies.

Health services

Patients analyze the items to improve hospital treatment, detect diseases and optimize the distribution of resources.

Financing and bank

Financial institutions use analytics to detect fraud, assess credit risk and predict trends for the stock market.

Retail and e-commerce

Online stores personalize recommendations using data analysis; customers improve the connection and increase sales.

Sports and entertainment

Team and media companies analyze players' performance and public engagement to increase the experiences and maximize profits.

How to Start with Data Analysis

Learn the Basic ThingsStart with basic statistical concepts, computer structures and principles for business intelligence.

Master Data Tools and TechnologiesFamiliarize yourself with the equipment as:

Python and R for programming

SQL for database administration

Tableau and Power BI for visualization

Work on real projectsUse your skills by analyzing the dataset, identifying the pattern and creating a report. Platforms like Kagal provide good practice opportunities.

Best Data Analysis Course registered on onlineA structured online course will provide step-by-step learning, projects and industry insights to increase your expertise.

Make a portfolio and search for jobs

Perform your computer projects on platforms such as Github and LinkedIn to attract the recruitment. Find the entry-level analyst roles for experience.

Conclusion

Data analysis is a game-skinned process that helps companies optimize operations, predict trends and make better decisions. If you are emotional when it comes to date-driven insights and problems, learning data analysis is a valuable investment. Join the best data analytics course online today and take the first step towards an exciting career in this rapidly growing field!

[jobsthe24]

Interview Preparation and Common Questions for Freshers

For freshers entering the job market, the interview is often the first major hurdle to overcome in securing a position. Proper preparation can make the difference between a successful interview and one that leaves you wondering what went wrong. This guide will focus on how to prepare for interviews effectively and cover some of the most common questions asked during job interviews for freshers.

1. Understanding the Importance of Preparation

An interview is a conversation where an employer assesses your suitability for a role, and you, in turn, evaluate whether the company and the job align with your aspirations. Preparation is key to making a strong first impression and showcasing your strengths. Without it, even the most qualified candidates may struggle to stand out. Here��s why preparation matters:

Confidence: Being well-prepared reduces nervousness and boosts your confidence. It gives you a clear sense of your qualifications, making it easier to articulate why you're the right fit.

Knowledge of the Company: Employers appreciate candidates who show that they’ve done their homework about the company and the role. This shows genuine interest in the opportunity.

Anticipating Questions: While you can’t predict every question, you can prepare for the most common ones, giving you a better chance to respond thoughtfully and concisely.

2. Researching the Company and Role

A significant part of your preparation should involve researching the company and understanding the role you're applying for. Here’s how to go about it:

Company Website: Visit the company’s official website to learn about its mission, values, services, and recent news. This will help you understand their culture and vision.

Job Description: Read the job description carefully. Highlight the key skills and qualifications needed, and prepare examples from your past experiences (internships, projects, or academic work) that align with these requirements.

Social Media: Check the company’s social media profiles, such as LinkedIn, Twitter, or Facebook, to gain insight into its public image and any recent updates or achievements.

Having a deep understanding of the company will enable you to craft tailored answers and demonstrate that you're invested in the opportunity.

3. Common Interview Questions and How to Answer Them

While interviews can be unpredictable, certain questions are commonly asked. Let’s review some of the most frequently posed questions and the best ways to answer them:

Tell me about yourself.

This is one of the first questions you’ll likely encounter. It’s an opportunity to give a brief, structured overview of your background and achievements. Focus on the following elements:

Education: Mention your academic background, especially if you’ve taken courses or projects relevant to the job.

Skills: Highlight key skills and strengths, particularly those that align with the job description.

Why this role: Conclude by explaining why you’re excited about this position and how it fits into your career goals.

Example: "I am a recent graduate with a degree in Computer Science from XYZ University. During my studies, I developed a strong foundation in programming languages such as Java and Python, and I had the opportunity to work on a project focused on web development. I'm excited about this role because it allows me to apply my technical skills in a professional setting while contributing to innovative projects."

Why should we hire you?

This question gives you a chance to sell yourself. Focus on your strengths, achievements, and unique qualities. Highlight your skills, enthusiasm, and how your background aligns with the company’s needs.

Example: "I bring a strong combination of technical and interpersonal skills. I’m eager to learn, adaptable, and a team player. I believe my ability to collaborate effectively in group settings, coupled with my technical knowledge in data analysis, would make me a valuable asset to your team."

What are your strengths and weaknesses?

When discussing strengths, choose qualities that are relevant to the job and provide examples. For weaknesses, focus on an area of improvement and show how you’re working on it.

Example Strength: "One of my strengths is my ability to stay organized and manage my time effectively. During my internship, I was able to juggle multiple projects simultaneously while maintaining attention to detail and meeting deadlines."

Example Weakness: "I sometimes struggle with delegating tasks because I like to ensure everything is done to a high standard. However, I’ve been working on improving my delegation skills by collaborating more with teammates and seeking their input, which has been beneficial for project efficiency."

Where do you see yourself in five years?

Employers ask this to gauge your long-term goals and whether they align with the company’s vision. It’s important to show that you’re thinking about growth, but also that you’re committed to contributing to the company’s success.

Example: "In five years, I see myself in a leadership role, contributing to the development of innovative projects. I hope to continue building my skills and knowledge in this field, while also mentoring junior team members."

Tell us about a time when you faced a challenge. How did you handle it?

Behavioral questions like this assess your problem-solving abilities and how you handle challenges. Use the STAR method (Situation, Task, Action, Result) to structure your response:

Situation: Describe the context.

Task: Explain the challenge you faced.

Action: Detail the steps you took to address it.

Result: Share the outcome, emphasizing positive results.

Example: "During my internship, I was tasked with managing a client’s website redesign. The project had tight deadlines, and there were frequent changes in client expectations. I organized regular meetings with the client to clarify requirements and reallocated tasks among the team to ensure the project stayed on track. The result was a successful launch within the deadline, and the client was very satisfied with the final product."

Why do you want to work here?

This question tests whether you’ve researched the company and are genuinely interested in the position. Link your motivations to the company’s values or the role’s opportunities.

Example: "I’m particularly drawn to your company because of its commitment to sustainability, which aligns with my personal values. I’m also excited about the opportunity to contribute to the innovative work your team is doing in the tech industry."

4. Practice Makes Perfect

Once you’ve prepared answers for common questions, practice them aloud. Mock interviews with a friend or mentor can simulate the interview environment and help reduce nervousness. Rehearse both your responses and body language. It’s important to sound natural and confident, so avoid memorizing answers verbatim.

5. Questions to Ask the Interviewer

At the end of the interview, you’ll likely be asked if you have any questions. Asking insightful questions shows your interest and helps you learn more about the company. Some great questions to ask include:

"Can you tell me more about the day-to-day responsibilities of this role?"

"How do you measure success in this position?"

"What opportunities for growth and development are available?"

Conclusion

Interview preparation is crucial to securing your first job. By researching the company, practicing common questions, and showcasing your strengths, you’ll be able to make a positive impression on potential employers. Remember, interviews are not just about answering questions but also about presenting yourself as a capable and enthusiastic candidate. With the right preparation, you'll be ready to take on any interview with confidence and ease.

[shalu620]

Kickstart Your Career in Python: A Guide for Freshers

Wondering if you can land a job in Python as a fresher? The answer is a definite yes! Python's popularity and demand in various industries make it a great choice for beginners. Here’s a step-by-step guide to help you get started. Considering the kind support of Learn Python Course in Pune, Whatever your level of experience or reason for switching from another programming language, learning Python gets much more fun.

1. Master the Basics of Python

Begin your journey by learning the core concepts of Python. Get a strong grasp on variables, data types, control structures, functions, and object-oriented programming. Utilize the wealth of online resources available, such as free tutorials, online courses, and comprehensive books. Platforms like Codecademy, Coursera, and Python.org are excellent starting points.

2. Build Practical Projects

Gaining hands-on experience is vital. Start by creating small projects that allow you to apply your knowledge. These can be simple scripts to automate tasks or more complex applications like web apps using Django or Flask. The more projects you work on, the more proficient you will become.

3. Explore Libraries and Frameworks

Python’s versatility comes from its extensive libraries and frameworks. Depending on your interests, familiarize yourself with key libraries. For data science, learn Pandas and NumPy. If machine learning interests you, explore TensorFlow or scikit-learn. For web development, get to know Django and Flask.

4. Contribute to Open Source Projects

Engage with the open-source community by contributing to projects. This experience will help you understand how large codebases work, enhance your problem-solving skills, and improve your ability to collaborate with other developers. Plus, it adds impressive entries to your portfolio. Enrolling in the Best Python Certification Online can help people realise Python’s full potential and gain a deeper understanding of its complexities.

5. Showcase Your Work

Create a GitHub account and upload your projects. A well-maintained GitHub profile serves as a portfolio that demonstrates your skills and dedication. Employers often look at GitHub profiles to assess candidates, so this can significantly boost your job prospects.

6. Seek Internships and Freelance Gigs

Look for internships or freelance work to gain practical experience. Even if these positions are unpaid at first, the experience will be invaluable. Platforms like Upwork, Freelancer, and Internshala are good places to find such opportunities. Internships and freelance work enhance your resume and provide real-world experience.

7. Network with Professionals

Networking can open many doors. Join Python communities both online and offline. Platforms like Stack Overflow, Reddit, and local meetups offer great opportunities to connect with other Python enthusiasts. Networking helps you stay updated with industry trends and learn from others’ experiences.

8. Start Applying for Jobs

Once you have a solid understanding of Python and a portfolio of projects, start applying for entry-level positions. Customize your resume and cover letter to highlight your Python skills and projects. Use job boards like LinkedIn, Indeed, and Glassdoor to find opportunities. Persistence is key; keep applying and refining your approach.

Conclusion

Getting a job in Python as a fresher is definitely achievable with dedication and the right strategy. Keep learning, practicing, and connecting with others in the field. Your hard work will pay off, and soon you'll find yourself embarking on an exciting career in Python programming. Good luck!

By following these steps, you'll set yourself up for success in the Python job market as a fresher. Stay committed to improving your skills, and the right opportunities will come your way.

[24678--577to]

Machine Learning in Education System

Source By LinkedIn

Machine learning has the potential to significantly impact the education system by augmenting traditional teaching methods, personalizing learning experiences, and providing valuable insights to educators. Here are some ways machine learning is being used in education:

Personalized Learning: Machine learning algorithms can analyze vast amounts of student data, such as performance, learning style, and preferences, to create personalized Cryptocurrency Prices and News learning paths for individual students. This allows students to learn at their own pace and receive tailored content and feedback to maximize their learning outcomes.

Intelligent Tutoring Systems: Intelligent tutoring systems leverage machine learning techniques to provide adaptive and interactive learning experiences. These systems can assess a student's knowledge, identify areas of weakness, and provide targeted support and feedback. By Machine Learning adapting to each student's needs, intelligent tutoring systems can enhance the effectiveness of instruction.

Automated Grading and Feedback: Machine learning algorithms can automate the grading process for assignments, quizzes, and exams. This not only saves time for educators but also provides students with immediate feedback, enabling them to identify areas for improvement. Automated grading can handle objective assessments like multiple-choice questions and can even be extended to assess written responses using natural language processing techniques.

Predictive Analytics: Machine learning models can analyze historical data to predict student outcomes, such as academic performance, dropout rates, and behavior patterns. Educators can leverage these insights to identify at-risk students and provide timely interventions to improve their chances of success. Predictive analytics can also help with resource allocation and educational planning.

Recommender Systems: Machine learning-based recommender systems can suggest appropriate learning resources, such as books, articles, videos, or online courses, based on a student's interests, learning style, and past performance. These recommendations can help students discover new materials and enhance their learning experience.

Natural Language Processing: Natural Language Processing (NLP) techniques enable machines to understand and generate human language. NLP can be used to develop intelligent chatbots or virtual assistants that can answer students' questions, provide guidance, and offer support. These systems can be available 24/7, providing immediate assistance and reducing the burden on teachers.

Data-Driven Decision Making: Machine learning facilitates data analysis and can assist education policymakers and administrators in making informed decisions. By analyzing data on student performance, attendance, and engagement, machine learning algorithms can identify trends, patterns, and areas for improvement, helping institutions optimize their educational strategies and resource allocation.

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[asquaretechnologies]

Overview: A career transformation can be a confusing but rewarding journey, especially if you are transitioning from a non-IT background to the field of analytics. In this blog, we will explore the steps, skills, and insights needed to become a successful person in the world of analytics, irrespective of any background.

Understanding the Analytics Landscape: Start by gaining a solid understanding of what analytics entails. Explore the different branches such as data analytics, business analytics, and data science. Identify the key roles and responsibilities within these domains and the industries that are actively seeking analytics professionals.

Identifying Transferable Skills: Assess your current skill set and identify transferable skills that can be leveraged in the analytics field. Skills such as problem-solving, critical thinking, attention to detail, and communication are valuable across various domains, including analytics.

Building a Strong Educational Foundation: While a formal education in analytics can be beneficial, it’s not always a prerequisite. There are numerous online / Offline courses, certifications, and workshops that cater to individuals with diverse backgrounds. Asquare Technologies offer comprehensive courses in analytics from Industry Experts.

Mastering Essential Tools and Technologies: Familiarize yourself with key tools and technologies used in the analytics field. Learn to work with analytics tools such as Python, R, SQL, and popular data visualization tools like Microsoft Power BI and Tableau. Asquare’s Online and Offline Programs and hands-on projects can help you build practical skills.

Networking and Industry Exposure: Networking is crucial for any career transition. Attend industry conferences, webinars, and local meetups to connect with professionals in the analytics field. Join online forums and communities like LinkedIn groups to stay updated on industry trends and connect with like-minded individuals.

Showcasing Your Skills Through Projects: Build a portfolio showcasing analytics projects you’ve worked on. This could include personal projects, case studies, or contributions to open-source initiatives. A strong portfolio is a tangible way to demonstrate your skills to potential employers. Asquare Technologies makes you to show case your skills with our Project Demonstration by each students after training completion.

Seeking Mentorship and Guidance: Reach out to professionals who have successfully transitioned from a non-IT background to analytics. Seeking mentorship can provide valuable insights, guidance, and a roadmap for your career transition.

Tailoring Your Resume and Cover Letter: Craft a compelling resume that highlights your transferable skills and showcases your commitment to transitioning into analytics. Tailor your cover letter to emphasize your motivation, skills, and any relevant experiences that align with the analytics field.

Preparing for Interviews: Asquare’s Mock Interview session makes you to be prepared for analytics-related interview questions. Practice answering questions that assess your problem-solving abilities, technical skills, and understanding of analytics concepts. Showcase your enthusiasm for learning and adapting to new challenges.

Continuous Learning and Adaptation: The field of analytics is ever-evolving. Commit to continuous learning and staying updated on the latest tools, techniques, and industry trends. This mindset will not only help you secure a role but also thrive in the dynamic analytics landscape.

Conclusion: Transitioning from a non-IT background to a thriving career in analytics is an achievable goal with the right mindset, skills, and strategic planning. Embrace the learning journey, stay persistent, and leverage your unique background as a strength in the analytics world. Your future in analytics awaits – Create the gateway to a rewarding and fulfilling career!

[tutort-academy]

7 Epic Platforms to Level Up Your SQL Game!!!!

If you're looking to level up your SQL skills, you're in the right place. SQL is a fundamental language for data professionals, and mastering it can open up opportunities in data science, data analysis, and other data-related roles.

But how do you go from learning SQL to becoming proficient in it?

The answer is simple: practice, practice, practice.

In this article, we'll explore the 7 best platforms to practice SQL and sharpen your data skills.

1. HackerRank: Coding Challenges for SQL Enthusiasts

HackerRank is a leading platform for coding challenges, and it offers a comprehensive SQL practice suite. Whether you're a beginner or an experienced SQL user, HackerRank has a wide range of questions to suit your skill level. You can filter the questions by difficulty (easy, medium, or hard) or by topic (select queries, joins, aggregations, etc.). Additionally, HackerRank offers Skills Certification Tests that allow you to test your SQL skills in a timed assessment format. With a free account, you can access the entire collection of practice questions and assessments.

2. SQLPad: Practice SQL with Real-World Scenarios

SQLPad is another excellent platform for practicing SQL. It provides practice questions in three broad areas: single-table operations, multi-table operations, and window functions. Each category includes questions of varying difficulty levels, allowing you to gradually progress from basic concepts to more advanced topics. SQLPad also offers industry-specific SQL coding questions, which can help you prepare for real-world scenarios. While some features require a paid account, you can access a selection of questions with a free account.

3. StrataScratch: Learn SQL with Real Company Interview Questions

StrataScratch is a popular platform that offers a vast collection of SQL interview questions. What sets StrataScratch apart is its focus on real company interview questions. You can filter the questions by topics, difficulty levels, and even specific companies. This platform provides a coding workspace that supports PostgreSQL, MySQL, and Microsoft SQL Server. If you're comfortable with Python, you can use the pandas library to solve the questions. With a free account, you can access a substantial number of questions and solutions.

4. DataLemur: Master SQL with Curated Interview Questions

DataLemur is a platform that specializes in curated SQL interview questions. Its collection includes questions that have appeared in interviews at top tech companies like LinkedIn, Tesla, Microsoft, and Walmart. With over 40 interview questions, DataLemur covers various SQL topics, including conditional aggregation, string and window functions, and cumulative sums. This platform can help you familiarize yourself with the types of questions commonly asked in SQL interviews.

5. LeetCode: Sharpen Your SQL Skills with Coding Challenges

LeetCode, a popular platform for coding challenges, also offers a diverse collection of SQL questions. You can find SQL problems of different difficulty levels and topics on LeetCode. The platform allows you to filter the questions by company tags, so you can practice questions asked by specific companies like Google, Amazon, Facebook, and more. While some features require a premium account, you can access a subset of the questions with a free account.

6. Mode: Learn and Practice SQL in a Structured Curriculum

Mode is a comprehensive platform that offers a structured curriculum for learning and practicing SQL. Its SQL tutorial covers three levels: basic, intermediate, and advanced. Each level includes multiple lessons with practice questions. Mode's curriculum covers a wide range of SQL topics, including select statements, joins, aggregate functions, subqueries, and window functions. This platform is an excellent choice if you prefer a guided learning experience with a well-organized curriculum.

7. SQLZoo: Learn SQL with Interactive Lessons and Assessments

SQLZoo is a learning and practice platform for SQL that offers interactive lessons and assessments. Its bite-sized lessons cover various SQL topics, starting from basic select statements to more advanced concepts like window functions. Each lesson includes short practice exercises to reinforce your learning. SQLZoo also provides dedicated assessments with more involved SQL questions to test your skills. This platform is ideal for hands-on learners who prefer interactive learning experiences.

Get Started with Tutort Academy Data Science Courses With Tutort Academy's data science courses, you can learn SQL and other essential data skills from industry experts and gain the confidence to excel in your data career.

Conclusion

Practicing SQL is crucial for improving your data skills and acing SQL interviews. The 7 platforms mentioned in this article offer a variety of practice questions and coding challenges to help you sharpen your SQL skills. From HackerRank's coding challenges to SQLPad's real-world scenarios and Tutort Academy's comprehensive data science courses, you have plenty of options to choose from. So, start practicing SQL today and take your data skills to the next level!

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How to leverage AI in finance with Christian Martinez

New Post has been published on https://thedigitalinsider.com/how-to-leverage-ai-in-finance-with-christian-martinez/

How to leverage AI in finance with Christian Martinez

Our sister community, Finance Alliance, recently held an Ask Me Anything (AMA) session inside our Slack community with Christian Martinez, Finance Manager at Kraft Heinz.

So, Christian answered members’ burning questions about how to successfully leverage AI tools in finance, and much more.

Below, you’ll find some highlights from the session, where Christian shared valuable insights and tips with Finance Alliance’s members. ⬇

The main use cases for using these types of tools, such as ChatGPT and Google Bard, include:

Identifying risks, opportunities, and trends.

Facilitating collaboration between departments.

Developing automatic AOP models.

Natural language processing (NLP).

Can ChatGPT interpret past trends and data to help automate financial forecasting?

I’ve seen that Google Bard, ChatGPT, and other similar language models are very powerful tools for many processes, but in order to help automate financial forecasting, they require an additional tool.

For example, Google Bard + Python.

How can ChatGPT help perform real-time financial analysis?

I see ChatGPT helping in two main ways:

Generating ideas on how to perform the analysis.

Providing Python code to use on Google Colab to perform real-time financial analysis.

How can you ensure buy-in from management in finance transformation projects/initiatives?

It’s really important to have that buy-in from management. In order to get it, you need to understand the ‘why are we doing this,’ and ‘why this matters.’ The answers will depend on the management and the project, but understanding those is key.

Another important thing you need to do is map your stakeholders/management people and understand how much interest and influence they have in your initiative.

I prefer to use Python (with Google Colab) for this! But for the MVM (minimum viable model), I sometimes use Excel.

I’m still in the process of exploring the potential of third-party tools. Right now, I’m using Tableau, Alteryx, Python, SQL, Microsoft Azure, and Power BI.

What are your top 5 methods to forecast data?

Random forests

Linear regression

Clustering

Monte Carlo simulation

Time series

How can AI help predict financial patterns?

They can primarily help through decision-making algorithms, predictive analytics, and automation.

What do you think are the best ChatGPT plugins for FP&A?

I have many articles on plugins:

3 Great ChatGPT Plug ins for Finance with Guide + Business Case

Generate your own ChatGPT Plug in guide in 3 Simple Steps

10 Amazing Ways to Use ChatGPT Plugins for Stock Analysis: Part 1

How can I use AI for financial modeling?

There are many good use cases for financial modeling. Some of the main ones are the creation of models (LBO, DCF, etc), research about models, generation of shortcuts guides on your financial modeling software, formula builder, etc.

Do you recommend using ChatGPT API in Python or is inaccuracy still a huge issue?

On its own, the API is the same as using the model on the OpenAI website. If you add things on top, it can then be valuable.

On accuracy, there are two things I’d recommend:

Use this before your prompts: “Act as a purely factual AI that doesn’t hallucinate. If you don’t know an answer or if it’s out of your training data, just say it…“

Treat ChatGPT as the most junior member of your team. They can contribute and help a lot, but you need to check their work before submitting it to your stakeholders/customers. Use your knowledge and expertise to assess the veracity of what they produce.

I mainly use Twitter and LinkedIn. I tend to follow a group of AI “general” influencers on Twitter, and then if I think it can be applied to finance and accounting, I post it on LinkedIn.

These are some of the accounts I follow:

About Christian Martinez

Christian Martinez is currently the Finance Manager at Kraft Heinz and has over six years of experience in financial planning and analysis (FP&A). He’s also the founder of The Financial Fox, a non-profit startup project which aims to democratize machine learning and data analysis.

Christian was named as one of the 30 under 30 in the Accounting and Finance industry in Australia in 2021. He also won the EMEA Data Democratizer Award in 2022 and was a finalist in the Young Leaders in Finance Awards in 2018.

Download Finance Alliance’s AI in Finance eBook

Artificial Intelligence (AI) is reshaping the finance industry and empowering finance teams to make smarter, data-driven decisions like never before.

But how can you incorporate AI into your financial workflow?

Welcome to the AI in Finance eBook, your trusted guide to merging AI’s vast potential with everyday finance operations such as forecasting, budgeting, analysis, and more.👇

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[willhiretemp]

Top 5 Use Cases of Machine Learning in Temp Hiring

The role of machine learning and artificial intelligence in temp hiring has the potential to change the hiring process. While the goal of recruitment has always been bringing the best candidates and jobs together, with an average job opening receiving 250 resume submissions, finding the best candidate from a massive applicant pool is easier said than done. Even after several levels of screening resumes and interviewing candidates, recruiting still remains an educated guess, a hope that the candidate will perform well within a given environment if they are hired..

52% of recruiters feel the hardest part of recruitment is finding the best candidates from a large applicant pool – (Source: Ideal’s Guide for Recruitment)

Who are the Stakeholders that would be affected by adopting Machine Learning and AI? Although technologies like AI and machine learning have been knocking on the doors of recruitment for quite some time now, most organizations are still reliant on keyword-matching algorithms which don’t take a candidate’s values, likes, and behavior into account. As a matter of fact, many organizations are still using job boards as their one-stop shop. These can be like a black hole for resumes and often feature job posts that have long been closed out.

Another consideration are the various players within the industry that include recruiters, MSPs, VMS and SMEs, all of which have their say in the recruiting process. With no set protocol for inclusiveness, the process is often laden with several loopholes which the candidates exploit to make their way inside. Technology could potentially help to streamline these various factions and allow for better identification of talent.

Companies Like Netflix & Google are Already Using Machine Learning in Recruitment!

Why is that top companies like Google and Netflix are always spot-on when it comes to finding the best temp and permanent talent? These companies have taken the same technology that is used in self-driving cars and recommendation engines and implemented in recruitment. Yes, we’re talking about machine learning algorithms that can train themselves over time to predict future trends. The more data you supply to a machine learning system the better it performs. From anticipating the best sourcing channels for a job role to predicting candidate performance based on skill set, behavior, and values, these algorithms help organizations increase their talent quality while decreasing the time-to-hire.

Machine Learning could reshape every stage of Talent Acquisition

Below are the use cases for AI and Machine Learning divided into the five different stages of talent acquisition, and the possibilities for every stage.

Use Case 1: Talent Sourcing

Top firms are using machine learning algorithms that use predictive variables like social profile changes, job boards visits and tracking to segment qualified candidates on their likelihood of changing jobs. They then target these candidates on different platforms using targeted advertisements.

Not only this, ML algorithms can use data to identify the best sourcing channels for a particular job role. As a for instance, an algorithm could clarify that when sourcing Python programmers, tapping into GitHub communities might be even more effective than LinkedIn or other avenues.

Best tool: Entelo

Use Case 2: Job Requirement Posting

Ensuring that job requirements are presented to the right people on the right platform is critical to making good hires. By using machine learning algorithms you can track the visitors on your careers page or website, and then use cookies to track what other platforms these users visit and at what times. This information can then be used to post targeted job ads on the right platforms at the right time, thereby increasing the hit rate and decreasing the time-to-hire.

Based on candidate behavior and preference, some AI-based tools can also tell which keywords to use in job advertisements depending on the prospective candidate profile.

Best Tool – Textio

Use Case 3: Resume Screening

Machine learning can not only help you screen resumes for keywords but for meaning. There are plenty of ways to do so. You can benchmark current resumes against resumes that have been successful in the past. You can then sort candidates based on different parameters like values, behavior,and reputation in your database. Most importantly, by using ML algorithms you can remove bias from the hiring process.

Best Tool- Staffline Pro

Use case 4: Candidate Interviewing

Video interviewing using ML algorithms not only helps save time but also reflects on patterns that are hard to catch even by the most experienced recruiters. By using algorithms to analyze voice tone, body language, context, keywords, and words choice, these algorithms can segment candidates based on their proficiency, honesty, culture-fit, and many more parameters.

Using data from previous studies ML algorithms are now also being used to develop competency tests that assess candidates on number of traits like trust, sensitivity, communication, data interpretation etc.

Best Tool – Hirevue

Use case 5: Follow-up and On-boarding

By using AI chatbots in recruitment companies can answer any questions a candidate might have 24/7. These AI chatbots come with programmed responses to a set of frequently asked questions and learn to incorporate new responses based on chat history. By self-learning based on interactions they can reduce recruiter man-hours considerably.

For companies that use machine learning in every phase of recruiting, by the time a candidate is about to be on-boarded they have made a virtual profile of each candidate based on his or her profile, which helps them curate personal messages for every candidate.

Best Tool – Staffline Pro

There is no doubt that by using machine learning algorithms in talent acquisition, companies can make better hiring decisions whether it be sourcing, screening or onboarding. Technology has the potential to impact every part of the recruitment cycle and can considerably reduce the cost-to-hire. Data driven, consistent, and free from any bias, machine learning applications in recruitment might revolutionize the entire process.

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QA Engineer Remote 30 000 year USD

QA Engineer Remote 30 000 year USD Remote work is quickly becoming the default option for high tech jobs. Crossover is the platform for top paying full time long term remote work and now is a great time to get onboard. We are growing rapidly across nearly 50 different job positions. This listing is for our QA Automation Engineer position but we have found great applicants often have a current title of QA Engineer or similar so don’t be confused about that difference we are glad you found us. Hit “Apply” to learn more about this exciting opportunity. Crossover the world’s largest remotework company is looking for high performing QA automation engineers for long term full time roles. We offer 100 remotejobs working with the best talent from around the world. QA automation engineers perform thorough testing activity regimens for a portfolio of more than 100 different Cloud based Saas products. You are part of a team responsible for ensuring the highest quality of our products by using the latest technologies and toolsets. QA automation engineers are responsible for producing test automation scripts which provide coverage of the functionality of products you are responsible for. Apply now to start your long term career path with us and shape the futureofwork. Key responsibilities < strong>

Create and execute comprehensive test plans based on functional coverage< li>

Convert end to end user scenarios to test cases< li>

Create test automation scripts from test cases < li>

Ensure best practices are followed in our Automation test suites< li>

Conducts Performance testing by creating testing plans and executing them < li>< ul>Candidate requirements < strong>

2 years of QA experience Test cases automation and documentation< li>

1 years of software development experience in Java Typescript Python Ruby C < li>

Hands on experience in working with automation tools such as Protractor Selenium TestComplete Appium and JMeter< li>

Be knowledgeable about HTML DOM API Git and Jasmine< li>

Good proficiency in the English language < li>< ul>Nice to have

Bachelor’s degree in Computer Science Engineering or related fields< li>

Hands on experience profiling web pages< li>

Experience in transforming use cases into performance scripts using industry standard tools such as LoadRunner JMeter and Gatling< li>

Experience using industry standard APM tools such as NewRelic AppyDynamics DynaTrace< li>

Experience with using virtual environments source control remote development issue tracking product build and installation < li>< ul>What you will be doing < strong>As a QA automation engineer you will be creating automation test suites for a portfolio of more than 100 different cloud based Saas products across different technologies. Your daily activities include setting up the test environments automating test cases and performing manual tests if necessary. Also you are responsible for transforming use cases into performance scripts. You work with the best test automation engineers around the world and use different automation tools like Protractor Appium RestAssured. This job offers the opportunity to learn from the best QA software architects around the world to write test automation scripts and use multiple platforms like JIRA and TestRail. You will have daily and weekly targets to work towards and you will receive regular feedback and coaching related to your performance. You will also deliver technical feedback and specific coaching to others in your team. There is so much to cover for this exciting role and space here is limited. Hit the Apply< strong> button if you found this interesting and want to learn more. We look forward to meeting you! What to expect next

You will receive an email with a link to start your self paced online job application.< li>

Our hiring platform will guide you through a series of online “screening” assessments to check for basic job fit job related skills and finally a few real world job specific assignments.< li>

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First emails may take up to 15 minutes to send refresh and check again.< li>

Second check your spam and junk folders for an email from Crossover.com mark as “Not Spam” since you will receive other emails as well.< li>

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If all else fails just visit https jobs.crossover.com directly search for this job and click “Apply”. You will be prompted to reset your password if you already applied using LinkedIn EasyApply. < li>< ul>Crossover Job Code LJ 3368 SA Al madin QaEngineer.008 * راتب مجزي جداً. * مكافأت و حوافز متنوعة. * توفير سكن مؤثث أو بدل سكن. * أنتقالات أو توفير بدل عنها. * توفير تذاكر السفر لمن يشغل الوظيفة و عائلته. * نسبة من الأرباح الربع سنوية. * أجازات سنوية مدفوعة الراتب بالكامل. * مسار وظيفي واضح للترقيات. * بيئة عمل محفزة و مناسبة لحالة الموظف. * تأمين طبي للموظيف و عائلته. * تأمينات أجتماعية. التقدم و التواصل مباشرة دون و سطاء عند توافر الألتزام و الجدية التامة و المؤهلات المطلوبة علي: jobswzayef@gmail.com

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How to Hire a Great Python Developer

Why Python?

The main focus of every industry or organization is a fast development to get succeed in the current market trends. There are several reasons python is a popular language among developers:

· It is easily understandable language with simple syntax

· It has a huge number of libraries which makes it easily accessible to developers

· It can handle both simple and complex tasks

· It has a huge community support to solve all the queries related to Python

Python is one of the most loved and popular programming languages among developers as per the reports.

Read: TOP 10 PYTHON TRAINING INSTITUTES IN BANGALORE

Which skills are important while choosing a Python developer?

1)    Django

2)    Machine Learning and AI

3)    Flask

4)    React

5)    MySQL

6)    Deep Learning

7)    Analytical Skills

8)    Communication Skill

Which Skills are required for an entry-level Python developer? Exp: 0 to 2 years

-An entry-level Python developer position must have the following skills:

-Basic Knowledge of Python Programming

-General Python syntax

-Data structure symbols

-Basic knowledge of SQL

-Basic CVS skills

-Strong knowledge of any popular Python framework

-Candidate should have done any project on python and also candidates must be able to make a simple web app from scratch.

-You can also check whether a candidate has done any Python Certification Course or not

Which Skills are required for a mid-level Python developer? Exp: 3 to 6 years

Mid-level Python developer position must have the following skills:

-Strong knowledge on the following terms: 

Object-oriented design

Coding

Test Patterns

-Experience of software development in python and building Big Data solutions

-Good Experience in building and maintaining software platforms

-Exposure of a cloud computing service will be an added advantage

Which Skills are required for a senior Python developer? Exp: 6+ years

Senior Python developer position must have the following skills:

Expertise in writing complex logic in Python as per the requirement

Awareness of front-end technologies such as JavaScript, HTML5, and CSS3

The expertise of object-relational mapper (ORM) libraries

Experience in Query languages like SAS, SQL, and Hive and in data visualization tools such as Tableau and Qlik

Strong Knowledge of Big Data technology such as Pig, HDFS, Hive, Spark, and Scala

Top companies hiring Python developers

Some top companies hiring for Python Developer with good salaries are Instagram, Spotify, Amazon, Survey-Monkey, Facebook, Google, YouTube, Quora, Dropbox, Yahoo, Reddit and Bitly

Hiring Python developers from StackOverflow

StackOverflow is basically a question and answer site for professional programmers. It is a great platform to hire amazing Python talent.

StackOverflow is a site where programmers ask and answer technical questions. To hire a candidate, we need to look at candidates answer for a specific question to see if they fit your requirements or not

On StackOverflow, developers are isolated based on their reputation scores and specific user badge. A perfect candidate must ranks high for both score and user badge. Each and every question has a specific tag associated with it and these tags can help you in finding developers as per your requirement.

Hiring Python developers from GitHub

GitHub is one of the world’s largest code hosts having approximately 31 million developers. On GitHub, you can analyze developers profile to get information about their knowledge. If you are shortlisting profiles on GitHub first make sure that candidate is open to recruiters.

After that, follow these steps to find the best talent on GitHub:

First of all, create a profile on GitHub

After profile creation, search for 3 parameters- 1) language 2) location and 3) followers

Before connecting with any potential Python developer on GitHub, you must remember a few things.

 1.  Check repositories to familiarize yourself with their work which will be mutually beneficial as you can sort out candidates who will be not a good fit for the job role.

2.  Cross-check their profiles on either LinkedIn to make sure if they would be a perfect fit for the job role or not

3. Don’t judge candidates based on their profile completion. Sometimes some developers don’t share their code publicly for security purposes.

4.  Also, don’t judge a candidate on their social following count as it never reflects anything about their skills.

There are some more important factors while hiring a Python developer like how you are presenting a job description (JD), you need to design recruiter email templates and if needed you have to set some assessments for entry-level, mid-level and for senior python developer. Interview questions also play a very important role in hiring Python developer so one should get ready with all the questions and logic associated with it.