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Data Analytics

(Available both Online & Offline)

In today’s digital world, data is the key to making informed business decisions. This course is designed to equip you with the skills to analyze, interpret, and visualize data effectively. Whether you’re a beginner or looking to sharpen your analytics skills, you’ll learn essential tools like Excel, SQL, and Power BI, and gain insights that drive business success. Join us and start transforming raw data into valuable insights!

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COURSE OUTLINE

ADVANCED EXCEL

  1. Excel Functions, including functions like “IF” VLOOKUP, and Index Match
  2. Use of formulas to perform complex calculation
  3. Test function to clean and manipulate data effectively
  4. Create and customized dynamic and combo charts for improved data visualization and dashboard development
  5. Creating and utilizing Pivot Table
  6. Automation with Macros and VBA

MYSQL

  1. Introduction to database and its application
  2. Real-world application of and uses of datasets
  3. Overview of SQL AND MYSQL
  4. MYSQL and Workbench
  5. Data types and Mysql commands
  6. Data Integrity and Constraints
  7. Mysql Clauses and their application
  8. Real-world application and procedures in Mysql

POWERBI AND DATA VISUALIZATION

  1. Introduction to POWERBI
  2. POWERBI : A comprehensive Guide to Data Visualization and Analytics
  3. POWERBI ecosystem and data analysis visualization
  4. Data transformation and preparation techniques using power queries
  5. Data modeling and visualization
  6. DAX syntax and functions for advanced analytics
  7. What-if analysis and scenario Manager
  8. Utilizing AI Features and key influencers
  9. Integrity Data from multiple sources
  10. Real-world application, publishing and sharing reports

DATA ANALYSIS WITH PYTHON: Introduction to NUMPY

  1. Introduction to Python Programming Basics and object oriented programming
  2. Functions and file handling using python
  3. Comprehensive Array fundamentals
  4. Perform Mathematical and Statistical Operations
  5. Exploring advanced functionalities like reshaping, flattering, conditional selection and handling missing values
  6. Introduction to Pandas for Data Manipulation
  7. Working with data frames, and series
  8. Data Transformation and Manipulation
  9. Visualization with Matplotlib
  10. Matering data presentation techniques
  11. Execute a real-world data analysis project

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