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Accelerate Your Career with our Data Analytics Course Online

Welcome to AI4Infinity, the leading destination for comprehensive data analytics course online. Whether you want to advance your career as a data analyst or dive into the exciting world of data analytics, our online courses will give you the skills and knowledge you need to succeed in this fast-growing field. Our data analyst online classes are tailored to the needs of both beginners and experienced professionals. Our curriculum focuses on hands-on, hands-on learning, covering everything from the basics of data analytics to advanced techniques and tools used in the industry today.

At AI4Infinity, we understand how important flexibility is in learning. That's why our online data analytics courses are structured to fit your busy schedule. Convenient online access allows you to study anytime, anywhere, at your own pace.


Joining our data analysis classes online opens a world of opportunities in various job designations, including:

  • Data Analyst
  • Business Analyst
  • Data Architect
  • Data Engineer
  • Business Intelligence Analyst
  • Data Scientist
  • Database Administrator
  • Statistician
  • Data and Analytics Manager


Entry-level data analysts (up to 1 year of experience) can earn between $45,000 and $65,000 per year, Mid-level data analysts (2-5 years of experience) can earn between $60,000 and $95,000 per year, Senior-level data analysts (6 or more years of experience) can earn between $90,000 and $140,000 per year.

What you'll get

Master Excel and Data Management

Learn spreadsheet operations, data formatting, sorting, filtering, and data validation in Excel. Explore mathematical and statistical functions, pivot tables, and advanced Excel features.

Harness the Power of Power BI

Gain expertise in using Power BI for business intelligence. Understand Power Query Editor, DAX, time intelligence functions, and text functions. Learn to create reports and dashboards.

Database Management with MySQL

Master MySQL, including data types, SQL commands, joins, constraints, views, indexes, stored procedures, and more. Learn to work with data, handle exceptions, and use sub-queries.

Data Visualization with Tableau

Discover Tableau's interface and connect to various data sources. Explore data calculations, dashboard development, and data visualization techniques. Create a wide range of charts and visualizations.

Python for Data Analytics

Get acquainted with Python programming, Anaconda Navigator, and data types in Python. Learn to work with strings, lists, loops, and libraries like Pandas, NumPy, Matplotlib, and Seaborn.

Statistics and R Programming

Explore descriptive and inferential statistics. Understand hypothesis testing, confidence intervals, and estimation theory. Additionally, learn R programming, data types, operators, functions, and data visualizations.

Course Content

  • 1. Introduction of Spreadsheet Application Worksheet Operations
  • 2. Clipboard
  • 3. Data Formatting
  • 4. Naming Range
  • 5. Data Management In Excel
  • 6. Sorting Filtering data
  • 7. Data validation
  • 8. Data consolidation Formulas Auditing
  • 9. Formatting and conditional formatting
  • 10. Lookup functions
  • 11. Mathematical Functions Statistical Functions Text Functions
  • 12. Date and Time functions
  • 13. Financial functions
  • 14. General functions
  • 15. Referencing
  • 16. Security of Workbook & Worksheet Pivot tables
  • 17. Charts In Excel Pivot Query Power Pivot Power Pivot Macro
  • 18. Time Saving Tips & Tricks. /Shortcuts

  • 1. Introduction to Business Intelligence
  • 2. Introduction to Power BI
  • 3. What is Power BI ? Why Power BI?
  • 4. Features of Power BI Power BI Services
  • 5. Power BI Components Building Blocks of Power BI
  • 6. Architecture of Power BI
  • 7. Power BI Desktop Installation Creating Report in Power BI
  • 8. Shaping Data Power Query Editor
  • 9. Data Model in Power BI DAX in Power BI
  • 10. Time Intelligence Functions Date and Time Functions
  • 11. Text Functions
  • 12. Logical Functions
  • 13. Math & Statistical Functions Filter Functions
  • 14. Project In Power BI
  • 15. Power BI Dashboard
  • 16. Power BI Interview Question

  • 1. Introduction to MySQL ,RDBMS and Installation of MySQL Workbench Indroduction to MySQL Data Types and Commands
  • 2. DDL Commands
  • 3. DML Commands
  • 4. DQL Commands and Different Operators
  • 5. TCL Commands
  • 6. Group By / Aggregate Functions
  • 7. Joins in MySQL
  • 8. Case When Then Expression and Handling NULL Values
  • 9. MySQL Constraints
  • 10. Views and Indexes in MySQL Stored Procedure in MySQL
  • 11. Exception Handling in MySQL Sub-query in MySQL
  • 12. User Define Function, Window Functions in MySQL Union, Union All, Handling Duplicate recoreds String Functions and Date Time Functions
  • 13. Triggers in MySQL

  • 1. Introduction Tableau
  • 2. Installing Tableau
  • 3. Interface of Tableau (Layout, Toolbars, Data Pane, Analytics Pane, etc.) Connecting to Excel, CSV Text Files
  • 4. Connecting to Databases Tableau field types
  • 5. Live vs extract connection Working with Data
  • 6. Analyzing
  • 7. Formatting
  • 8. Introduction to Calculations
  • 9. Dashboard Development Sharing
  • 10. Data Calculations Aggregate Calculations User Calculations Table Calculations
  • 11. Logical Calculations String Calculations Number Calculations Type Conversion Parameters
  • 12. Filtering Conditions Filtering Measures Histograms
  • 13. Sorting
  • 14. Grouping
  • 15. Sets
  • 16. Tree maps, word clouds and bubble charts
  • 17. Pareto Charts
  • 18. Waterfall Charts
  • 19. Bump Charts
  • 20. Funnel Charts
  • 21. What is a dashboard?
  • 22. Building and formatting a dashboard using size, objects, views, filters, and legend.

  • 1. Introduction to Python Programming and Installation of Anaconda Navigator Variables and Data Types in Python
  • 2. String , List and Tuple Data Types
  • 3. Sets and Dictionaries
  • 4. Indentation in Python and Conditional Statements
  • 5. Loops in Python (For, While)
  • 6. User Defined Functions and Lambda Functions in Python Libraries in Python : Pandas
  • 7. NumPy
  • 8. Matplotlib & Seaborn

  • 1. Descriptive Statistics
  • 2. Inferential Statistics
  • 3. Confidence Interval
  • 4. Testing of Hypothesis -Z test,T test, Anova
  • 5. Estimation Theory

  • 1. Introduction to R Programming , Installation of Rstudio
  • 2. Variables and Different Data Types in R Programming
  • 3. Different operators in R Programming
  • 4. Conditional Statememts and Looping Statements in R Programming
  • 5. User Defined Functions and Joins in R Programming
  • 6. Working with Data Sets and Data Visualizations using Different Libraries

Learner Benifits

Tailored Learning Experience

Our institute offers individualized lessons specifically tailored to each learner’s needs. We enable every student to realize his or her maximum potential as well as achieve their career objectives through customized curricula, flexible educational alternatives and personalized assistance.

Industry-Embedded Training

As part of our curriculum, we work with field professionals so that it remains current, practical and reflective of the trends in the job market. Students get hands-on experience applying the latest tools and techniques, which prepares them to succeed in their chosen fields.

Extensive Placement Support

After graduation, our students can rely on comprehensive placement support services that allow them to enter meaningful employment. From resume writing workshops to interview coaching sessions, our career services staff is dedicated guiding students towards finding a job.

Expert Mentorship

Students have opportunities to interact with experienced professionals who provide invaluable advice about what they are learning in college. These mentor relationships enhance learning while acting as conduits for networking and advancement in careers.

Large Alumni Network

We are proud of owning one of the biggest alumni networks in our region comprising successful professionals in other industries also. As a student you will get access to this network providing you with valuable connections and potential career pathways after training


Data science is a multidisciplinary field that involves using techniques from statistics, machine learning, computer science, and domain expertise to extract insights and knowledge from data.
AI is a broad field of computer science that focuses on creating systems and machines that can perform tasks that typically require human intelligence, such as understanding natural language, recognizing patterns, and making decisions.
A strong foundation in mathematics, particularly statistics and linear algebra, along with programming skills (usually in languages like Python or R), is essential. Knowledge of computer science fundamentals is also valuable.
Machine learning is a subset of AI that encompasses various techniques for making predictions and decisions from data. Deep learning is a subfield of machine learning that focuses on using neural networks, particularly deep neural networks, for tasks like image and speech recognition.
The demand for data scientists and AI professionals is high across various industries, including finance, healthcare, tech, and more. Career prospects include roles such as data analyst, machine learning engineer, data engineer, AI researcher, and data scientist.
Common tools include Python/R, libraries like TensorFlow and scikit-learn, Jupyter notebooks, and data visualization tools like Matplotlib and Tableau. Cloud platforms like AWS, Azure, and Google Cloud are also important.
You can work on personal projects, participate in online competitions (e.g., Kaggle), internships, and contribute to open-source projects. Online courses and bootcamps also offer hands-on experience.
Showcase your projects, including problem statements, data preprocessing, modeling techniques, and results. Explain your approach and the impact of your work. A well-documented portfolio is essential for job applications.
While advanced degrees can be beneficial, many roles in data science and AI can be entered with a bachelor's degree. Continuous learning, certifications, and practical experience are also highly valued.
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