#Learn tableau

[cavillionlearning]

Industry-Leading Visualization with Tableau Data Visualization

1. User-Friendly Interface: The intuitive design allows anyone to easily start visualizing data.

2. Seamless Integration: Connects easily with various data sources for efficient analysis.

3. Quick Insights: Generate actionable insights within minutes.

4. Integrated Collaboration Tools: Share dashboards and insights with your team effortlessly.

5. Regular Updates: Tableau continuously evolves with new features and improvements.

Want to take your skills to the next level? Join our 1-day Tableau Bootcamp on 2nd November (Online)!

[digitalmarketing6669]

Master Data Preparation in Tableau: Beginner’s Guide for 2024

[cacmsinsitute]

The Function of Data Analytics in Smart City and Urban Planning

As global urbanization accelerates, cities face new infrastructure, resource management, and quality of life concerns. To handle these complications, many governments are turning to data analytics, a strong tool that provides novel solutions for smart city programmes and urban planning. Data analytics promotes informed decision-making, operational efficiency, and sustainable urban development.

Enhancing Infrastructure Management

One of the most important uses of data analytics in smart cities is infrastructure management. City planners can monitor the status and use of infrastructure in real time by collecting and analyzing data from a variety of sources, including sensors, cameras, and GPS devices. This constant flow of information enables predictive maintenance, lowering the risk of unexpected breakdowns and optimizing resource allocation.

Smart grids, for example, use data analytics to balance energy supply and demand, resulting in fewer outages and more efficiency. Similarly, smart transportation systems analyse traffic patterns to alleviate congestion, shorten travel times, and improve public transportation services. These data-driven initiatives ensure that urban infrastructure is robust, efficient, and responsive to the requirements of its citizens.

Improving public services

Data analytics may also help improve public services by making cities more livable and responsive to resident requirements. Municipalities can better distribute resources and identify areas that need attention by analyzing data from social media, public input platforms, and service consumption statistics. This data-driven strategy improves services including trash management, emergency response, and public health.

For example, predictive analytics can be used to optimize waste collection schedules based on real-time bin fill levels, lowering costs and environmental effect. Similarly, emergency response teams can utilize data analytics to anticipate high-risk locations and better allocate resources, potentially saving lives and property.

Promoting Sustainability

Sustainability is a key component of smart city programmes, and data analytics is critical to meeting environmental goals. Cities can monitor air quality, water levels, and energy consumption using data from a variety of environmental sensors. This information is useful in developing plans to decrease pollution, conserve resources, and improve the general quality of the urban environment.

Smart water management systems, for example, use data analytics to detect leaks, forecast water demand, and optimize distribution, resulting in water conservation and cost reduction. Cities can also use data on energy consumption patterns to encourage renewable energy sources and execute energy-saving policies.

Facilitating Urban Planning

Data analytics greatly improves urban planning by allowing planners to construct more accurate and efficient plans. Geographic Information Systems (GIS) and other data-driven tools enable planners to visualize urban landscapes, simulate scenarios, and evaluate the impact of proposed developments. This enables educated decision-making that balances economic growth, environmental sustainability, and social equality.

Data analytics can also improve participatory planning by incorporating feedback from residents and stakeholders. Planners can ensure that urban development initiatives meet the requirements and preferences of their communities by analyzing feedback and engagement data. This collaborative approach generates a sense of ownership and inclusion among inhabitants.

Improving Quality of Life

Ultimately, smart cities and urban planning aim to improve citizens' quality of life. Data analytics helps achieve this goal by offering insights into numerous areas of urban living, such as housing affordability and public safety. Understanding inhabitants' needs and behaviors enables cities to adopt tailored initiatives that improve living circumstances and promote well-being.

Data analytics, for example, can be used to detect high-crime regions and design crime prevention and community policing plans. Similarly, analyzing data on housing markets can aid in the development of policies addressing affordability and accessibility concerns.

Conclusion

The incorporation of data analytics into smart cities and urban planning promises a disruptive approach to addressing the issues of modern urbanization. Cities may use data-driven insights to improve infrastructure management, public services, sustainability, efficient urban planning, and, ultimately, the quality of life for their citizens. As technology advances, data analytics will play an increasingly important role in building future cities. Investing in data analytics capabilities is not an option; it is a requirement for cities seeking to become smarter, more sustainable, and resilient.

Join the CACMS Institute for data analytics training.

CACMS Institute provides comprehensive data analytics training that will help you transform your profession. Gain practical experience and flexible scheduling to learn the skills required for smart cities and urban planning.

For further information, please contact us at +91 8288040281 or visit CACMS Institute Improve your career with the best data analytics courses in Amritsar.

[accelebrate]

Machine Learning Training for Non-Tech Professionals: How to Get Started

For non-tech professionals, venturing into machine learning can seem intimidating. Yet, this field is becoming more accessible, presenting exciting opportunities for those ready to tackle new challenges. This guide will help you navigate the transition into machine learning roles, providing you with the essential knowledge and resources to start your journey with confidence. By following these steps, you'll be well on your way to harnessing the power of machine learning to enhance your career.

Understanding the Basics

Before you jump into the deep end, it's essential to grasp the fundamentals of machine learning. Start with understanding what machine learning is: it's a branch of artificial intelligence (AI) that involves training algorithms to learn from data and make predictions or decisions without being explicitly programmed. The core concepts include supervised learning, unsupervised learning, and reinforcement learning. Familiarizing yourself with these basics will provide a solid foundation for further exploration.

Identify Your Goals

Next, define why you want to learn machine learning. Are you looking to enhance your current role, switch careers, or start a new project? Knowing your goals will help you choose the right learning path. For instance, if you're in marketing, you might focus on predictive analytics. If you're in finance, you might be more interested in risk modeling.

Leverage Online Resources

There is a wealth of online resources designed to make machine learning accessible to non-tech professionals. Platforms like Coursera, edX, and Udacity offer introductory courses that cover the basics of machine learning without requiring a deep technical background. Look for courses that offer practical exercises and real-world applications, which can help bridge the gap between theory and practice.

Start with Data Analysis

One of the most crucial aspects of machine learning is data analysis. Learning how to handle and analyze data will make the transition smoother. Tools like Excel, Google Sheets, and basic statistical software are great starting points. Once you're comfortable with data handling, you can move on to more advanced tools like Python or R, which are commonly used in machine learning.

Choose the Right Training Program

For non-tech professionals, choosing a comprehensive and supportive training program is vital. Look for programs that offer structured learning paths, hands-on projects, and personalized support. Accelebrate is a renowned provider in this space, offering a wide range of courses designed to cater to different levels of expertise and industry needs. Their courses are known for their practical approach and expert instructors, making them an excellent choice for those new to the field.

Stay Updated and Keep Learning

Machine learning is a rapidly evolving field, and continuous learning is essential. Stay updated with the latest trends, tools, and technologies by following industry blogs, subscribing to relevant journals, and experimenting with new techniques and algorithms.

In Conclusion

Transitioning into a machine learning role as a non-tech professional is entirely achievable with the right approach and resources. To further accelerate your learning journey, consider enrolling in a course with Accelebrate. Their extensive range of machine learning courses is tailored to help professionals from all backgrounds gain the skills they need to succeed in the world of data and AI.

Embrace the challenge, and you'll find that the world of machine learning is not just for techies—it's for anyone willing to learn and innovate. Happy learning!

For more details, visit: https://www.accelebrate.com/machine-learning-training

[the-awesomecosmos-studies]

Day 3/100 days of productivity | Wed 21 Feb, 2024

Long day at work, chatted with colleagues about career paths in data science, met with my boss for a performance evaluation (it went well!). Worked on writing some Quarto documentation for how to build one of my Tableau dashboards, since it keeps breaking and I keep referring to my notes 😳

In non-work productivity, I completed the ‘Logistic Regression as a Neural Network’ module of Andrew Ng’s Deep Learning course on Coursera and refreshed my understanding of backpropagation using the calculus chain rule. Fun!

[lohithkumar9011]

DATA ANALYTICS COURSE IN GANGTOK

Upgrade your career with DataMites Data Analytics Course in Gurgaon. Learn Python, SQL, Power BI, Tableau, and Machine Learning with expert-led training. Get hands-on experience, industry certification, and internship & job support. Limited-time 65% fee discount!

[lonestaracademy]

JUST PLACED AT PALLADIUM.

[kanikarawat758]

Free Data Science Courses to Build Your Career Skills

Introduction

Data science is transforming industries, making it one of the most in-demand skills in today's job market. With the global data science platform market projected to grow from $95.3 billion in 2021 to $322.9 billion by 2026 at a staggering CAGR of 27.7%, professionals with data expertise are in high demand. 

Free data science courses provide an excellent opportunity to upskill without financial barriers. They enable you to learn data science for free, covering everything from basic concepts to advanced techniques. This blog highlights top free resources, helping you kickstart or advance your career in this rapidly growing field.

Top Free Data Science Courses

Data Science is evolving rapidly, and finding quality resources for learning without paying is now easier than ever. Whether you’re new to Data Science or looking to expand your knowledge in specialised areas like Machine Learning or Data Visualisation, free online courses offer a fantastic opportunity to learn at your own pace. 

Here’s a comprehensive guide to the top free Data Science courses available. Each course provides a unique focus, giving you options to build your Data Science skills effectively and affordably.

Applied Data Science by Future Learn

Future Learn’s Applied Data Science course collaborates with Coventry University, the Institute of Coding, and Birkbeck University to introduce students to the practical aspects of Data Science. This beginner-friendly course emphasises Data Visualisation, Machine Learning applications, and clustering techniques.

Key Features

User-Friendly Platform: Future Learn offers an intuitive experience with flexible schedules and engaging video-based learning.

Focus on Applied Data Science: Practical examples help users apply Data Science methods to real-world business cases.

Self-paced Learning: Students can start anytime and learn at their speed.

Certificate Option: Obtain a certificate for an additional 6,222 ₹.

Accessible Topics: Covers geolocation data, feature extraction, and introductory Machine Learning.

Data Science Professional Certificate by IBM on Coursera

The IBM Data Science Professional Certificate on Coursera offers an in-depth curriculum spanning nine courses. This specialisation takes about 11 months to complete. It includes a capstone project designed to simulate real-world data challenges, making it one of the most comprehensive free courses in Data Science.

Key Features

Nine-Course Structure: Covers everything from basic Data Science concepts to advanced SQL and Python.

Capstone Project: Provides a simulated real-world experience.

Certificate Upon Completion: Receive a shareable certificate on Coursera upon successful completion.

Excellent Instruction Quality: Taught by experienced IBM professionals.

Career-Boosting Potential: Many students use this course as a launchpad for Data Science careers.

Data Science Course by Pickl.AI

Pickl.AI’s Data Science Course is structured into 11 modules, covering everything from SQL and Tableau to Machine Learning techniques. With hands-on exercises and real-world case studies, this course is designed for beginners and professionals looking to advance in Data Science.

Key Features

Extensive Modules: Includes 462 lessons on SQL, Python, Machine Learning, and more.

Real-Life Case Studies: Learn through practical examples and case studies.

Certification Available: Certification offered upon completion, enhancing employability.

Focus on Data Science Tools: Access high-demand tools like Tableau and Power BI.

Flexible Pace: Allows learners to move through modules at their own speed.

Introduction to Data Science by Alison

Alison’s Introduction to Data Science course is a quick, impactful introduction to core Data Science concepts. It’s highly rated among working professionals and provides insights into data structuring, Machine Learning basics, and essential Data Science processes.

Key Features

Quick Overview: Completes in 1.5 to 3 hours, ideal for busy professionals.

Beginner-Friendly: No prior knowledge is required, making it accessible to everyone.

Certification Included: Receive a certificate upon completion, adding value to resumes.

Focus on Practical Skills: Learn data extraction, modelling, and scientific methods.

User-Friendly Platform: Alison is known for its ease of use and career-focused course design.

Data Science and Machine Learning with Python by Skillshare

Skillshare’s Data Science and Machine Learning with Python course offers an immersive look into Python, regression models, and ensemble learning, with a two-week free trial for new users. Frank Kane, an expert with over nine years of experience at Amazon and IMDB, leads this course, making it an excellent option for in-depth Python training.

Key Features

Access with Free Trial: Skillshare’s two-week free trial allows full access to the course.

Professional Instructor: Frank Kane brings practical experience and industry insights.

In-Depth Python Training: Covers foundational Python skills and data manipulation.

Beginner-Friendly: No prior knowledge is needed to start.

10-Hour Format: Perfect balance of depth and accessibility, making it manageable for beginners.

Conclusion

Free data science courses provide an excellent pathway to upskilling and breaking financial barriers. With platforms like Future Learn, IBM, and Pickl.AI offering specialised modules, learners can grasp core concepts, explore advanced techniques, and boost their career potential. Start today and embrace the growing demand for data science skills in this dynamic, evolving industry.

[usadailynews24]

Celtic vs Rangers LIVE! Scottish League Cup Final Match

https://urlhub.pro/bebd30

[graymeadows]

Monday Breakfast 9/9/24

Greek omelette with sauteed spinach and garlic, Roma tomatoes, and generous amounts of feta. Black pepper and smoked paprika sprinkled on top. Served with a slice of potato bread toast with a drizzle of olive oil.

I must say, I'm shocked by how cooperative the eggs were during the folding and flipping process. This is my first omelette in years and I'm pretty pleased with how it turned out. The eggs are fluffy, the flavors don't overwhelm each other, and it folded really well! The sprinkle of smoked paprika added a little extra flavor and color to it, and the feta is so salty that I skipped using table salt altogether.

Next time I'll add red onion or shallots and I might try a different tomato.

Toast is toast. I like toast.

Tea is Orange Turmeric Ginger and yes, I am drinking a bucket of it.

Today's rating: 7/10

This morning's vape is Blue Mintz Live Resin by Cresco. Purchased with prescription for a medical condition at a legal dispensary. Don't vape underage. Your brains aren't done cooking yet.

Energetic, creative and focused. Happy and content. It creeps a bit. May get cracking on some art projects:)

Vape rating: 5/10

[cavillionlearning]

Why Learn Tableau? Here are 5 powerful reasons to get started with this industry-leading tool

1. Industry-Leading Visualization: Transform raw data into stunning visuals!

2. High Demand in Data Analytics: Tableau skills are highly valued in today’s job market.

3. Actionable Insights in Minutes: Make data-driven decisions faster.

4. User-Friendly Interface: Easy to learn, even for beginners.

5. Boost Your Career: Stand out in data roles and advance your career! Want to take your skills to the next level?

Join our 1-day Tableau Bootcamp on 2nd November (Online)!

[kavithahachion]

Tableau Training | Tableau Course| Tableau Certification - Hachion

Gain the expertise required to excel in the Tableau Desktop Certification with our in-depth Tableau training course. Sign Up Today!

For more details Enroll in the below link https://forms.gle/FaUfvedokw6b2AZAA

[cacmsinsitute]

Exploring Advanced Tableau Techniques for Improved Data Insights

Introduction:

Tableau has emerged as a powerful tool for visualizing and interpreting complex datasets in the dynamic world of data analysis. While beginners can quickly grasp the fundamentals of Tableau, mastering advanced techniques can significantly improve your ability to extract valuable insights from your data. In this article, we will delve into the realm of advanced Tableau techniques that will enable you to gain deeper data insights and unlock the full potential of this versatile data visualization tool.

Using Parameters and Calculated Fields: Parameters and calculated fields are essential tools for developing interactive and dynamic dashboards. Learn how to use parameters to provide user-driven data exploration, allowing viewers to adjust variables and instantly see the corresponding changes. Learn how to use calculated fields to perform complex calculations, build custom aggregations, and create sophisticated calculations that go beyond Tableau's built-in functions.

Advanced Data Blending and Joining: Tableau's data blending and joining capabilities extend beyond simple table connections. Learn advanced techniques for merging disparate datasets, dealing with granularities, and dealing with data with common and uncommon dimensions. Investigate data blending with multiple data sources and discover Tableau's true power in combining and visualizing diverse datasets.

Level of Detail (LOD) Expressions: In Tableau, Level of Detail (LOD) expressions allow you to perform calculations at various levels of data granularity. Dive into LOD expressions to perform complex aggregations, create custom dimensions, and generate insights that necessitate data analysis at various levels of detail. Learn how to use LOD expressions' flexibility and precision to answer specific business questions and gain deeper insights.

Advanced Visualisations and Dashboard Design: In addition to basic charts and graphs, Tableau provides a wide range of visualization options. Learn about advanced visualization techniques such as dual-axis charts, heat maps, tree maps, box plots, and more. Learn how to create interactive and user-friendly dashboards by incorporating features such as actions, filters, and parameter controls. Discover best practices for dashboard layout, storytelling, and incorporating interactivity to improve user engagement and comprehension.

Integrating Advanced Analytics: Tableau's integration with statistical and predictive analytics tools opens up a world of advanced analytics possibilities. Learn how to use R and Python scripts in Tableau to perform advanced statistical analysis, predictive modeling, and machine learning. Discover insights that go beyond traditional data visualization by combining the power of Tableau with advanced analytical techniques.

Advanced Mapping and Geographic Analysis: Tableau's mapping capabilities go beyond simple location plotting. Learn advanced geospatial analysis techniques such as spatial aggregations, custom geocoding, and data integration with GIS. Learn how to make interactive maps with layers, tooltips, and filtering options to visualize data in a spatial context and gain geographic insights.

Conclusion: By utilizing these advanced Tableau techniques, you can unlock the full potential of your data and gain deeper insights. Each technique, from parameters and calculated fields to advanced analytics and mapping, enables you to tackle complex data challenges and effectively communicate your findings. Utilize advanced Tableau techniques to turn your data into a compelling visual narrative that drives informed decision-making and uncovers valuable insights.

Are you ready to master Tableau? Join CACMS for a full course to unleash your data visualization abilities. Enroll now at http://cacms.in/

[actify-9090]

Intermediate Tableau Courses in Thane

Bridge the gap between basic and advanced skills with our intermediate Tableau courses in Thane! Enhance your knowledge, tackle more complex projects, and advance your data visualization capabilities. Sign up now and take your skills to the next level! #IntermediateTableau #DataSkills #Thane

For more Details

Company Name:-Actify Learning

Address:- 3rd Floor, Guruprerana,Opp. Jagdish Book Depot,Above Choice Interiors, Naik Wadi, Near Thane Station,Thane (W) 400602.

Contact No:-9867476400

Email ID:-info@actifyzone.com

Website Url:-https://www.actifyzone.com/learning

[sql-datatools]

Tableau 👉 Understanding and Key Features

[lohithkumar9011]

DATA ANALYTICS COURSE IN KOTA

Elevate your career with DataMites Data Analytics Course in Dehradun. Master Python, SQL, Power BI, Tableau, and Machine Learning with expert-led training. Gain practical experience, industry certification, and internship & job support. Limited-time 65% fee discount!