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Diploma in Data Analyst & Business Analytic Course

Diploma in Data Analysis Course

Diploma in Data Analyst & Business Analytic Course

A Diploma in Data Analyst & Business Analytics Course with professional coaching and training is available in Ahmedabad from Pluto IT Engineering & Multimedia Institute. To give students industry-relevant skills, our data analytics courses cover data visualisation, statistical analysis, Power BI, SQL, and predictive modelling. Being one of the best institutes in Ahmedabad, we emphasise practical experience and professional advancement through hands-on learning with real-world projects. Join our professional diploma program to further your career in data-driven decision-making if you’re searching for the best business analytics and data analytics courses in your area.

Diploma in Data Analyst & Business Analytic Course Module

  1. Introduction to Data Science
  2. Evolution of Data Science
  3. Big Data Vs. Data Science
  4. Data Science Terminologies
  5. Data Science Vs. AI/Machine Learning
  6. Data Science Vs. Analytics
  1. What Is ML? ML Vs. AI
  2. ML Workflow, Popular ML Algorithms
  3. Clustering, Classification And Regression
  4. Supervised vs. unsupervised
  1. Data Science in Finance and Banking
  2. Data Science in Retail
  3. Data Science in Health Care
  4. Data Science in Logistics and Supply Chain
  5. Data Science in Technology Industry
  6. Data Science in Manufacturing
  7. Data Science in Agriculture
  1. Introduction to excel
  2. Sort & Filter
  3. Text Functions
  4. Statistical Functions
  5. Logical Functions
  6. Conditional Formatting
  7. Index and Match
  8. Pivot Tables
  9. Regression
  10. Macros in Excel
  11. Getting Started With VBA
  12. Excel Charts & Smart Art Graphics
  13. How to Create Business Analytics Dashboards
  14. Advance formulas
  15. 7 days Advance V-LOOKUP Formulas
  16. Data Visualization using Excel
  17. Analysis report
  18. Project Task tracker Dashboard In Excel
  1. Introduction of Python
  2. OOP Concepts
  3. Programming Style
  4. Core python concepts
  5. Conditional Statements
  6. If, If- else, Nested if-else
  7. Looping, For, While, Nested loops
  8. Control Statements, Break, Continue, Pass
  9. String Manipulation
  10. Accessing Strings
  11. Basic Operations
  12. String slices
  13. Function and Methods
  14. Calling a function
  15. Types of functions
  16. Function Arguments
  17. Anonymous functions
  18. Class
  19. Object
  20. Attributes
  21. Inheritance
  22. Overloading
  23. Overriding
  24. Data Hiding
  25. Input & Output
  26. Exception Handling
  1. Python Pandas
  2. Pandas Introduction
  3. Pandas Getting Started
  4. Series
  5. Data Frames
  6. Read CSV
  7. Read JSON
  8. Analyzing Data
  9. Cleaning Data
  10. Cleaning Empty Cells
  11. Cleaning Wrong Format
  12. Cleaning Wrong Data
  13. Removing Duplicates
  14. Pandas Correlations 
  1. Matplotlib Introduction
  2. Pyplot
  3. Plotting
  4. Markers
  5. Line
  6. Labels
  7. Grid
  8. Subplot
  9. Scatter
  10. Bars
  11. Histograms
  12. Pie Charts
  1. Get Started
  2. Create Database
  3. Create Table
  4. MYSQL Insert
  5. MYSQL Select
  6. MYSQL Where
  7. MYSQL Order By & DESC
  8. MYSQL Delete
  9. MYSQL Update
  10. MYSQL Limit
  11. MYSQL Join
  1. MongoDB Get Started
  2. MongoDB Create DB
  3. MongoDB Collection
  4. MongoDB Insert
  5. MongoDB Find
  6. MongoDB Query
  7. MongoDB Sort
  8. MongoDB Delete
  9. MongoDB Drop Collection
  10. MongoDB Update
  11. MongoDB Limit
  1. R Get Started
  2. R Syntax
  3. R Comments
  4. R Variables
  5. R Data Types
  6. R Numbers
  7. R Math
  8. R Strings
  9. R Booleans
  10. R Operators
  11. R If…Else
  12. R While Loop
  13. R For Loop
  14. R Functions
  15. R Data Structures
  16. R Vectors
  17. R Lists
  18. R Matrices
  19. R Arrays
  20. R Data Frames
  21. R Factors
  22. R Graphics
  23. R Plot
  24. R Line
  25. R Scatterplot
  26. R Pie Charts
  27. R Bars
  28. R Statistics
  29. R Statistics Intro
  30. R Data Set
  31. R Max and Min
  32. R Mean Median Mode
  33. R Percentiles
  1. Introduction to Google Looker Studio
  2. Overview of data sources (Google Sheets, MySQL, etc.)
  3. Connecting to different data sources in Looker Studio
  4. Data visualization using Using charts, tables, and scorecards
  5. Designing Dashboards
  6. Ensuring accessibility and readability
  7. Managing access and permissions
  8. Case Study 1: E-commerce Sales Analysis
  9. Case Study 2: Marketing Campaign Performance
  10. Case Study 3: YouTube Channel Report
  1. Overview of Google Analytics
  2. Key Concepts and Terminology
  3. Setting Up Google Analytics for Your Business
  4. Understanding the Interface
  5. Creating and Configuring a Google Analytics Account
  6. Implementing Google Analytics Tracking Code
  7. Setting Up Goals and Funnels
  8. Linking Google Analytics with Other Google Tools (Google Ads, Search Console)
  9. Understanding User Behavior and Acquisition Metrics
  10. Analyzing Audience Reports (Demographics, Interests, Geo, Technology)
  11. Traffic Sources and Campaign Performance
  12. Behavior Reports (Site Content, Landing Pages, Site Speed)
  13. Real-Time Analytics
  1. Introduction to Google Search Console
  2. Verifying Website Ownership
  3. Performance Reports
  4. Index Coverage and Crawl Reports
  5. URL Inspection and Troubleshooting
  6. Security and Manual Actions
  7. Link Reports and External Links Analysis
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