Curriculum

  • 5 Sections
  • 17 Lessons
  • 10 Weeks
Expand all sectionsCollapse all sections
  • Module 1: Introduction to Business Analytics & AI
    4
    • 1.1
      What is Business Analytics? — Types (descriptive, diagnostic, predictive, prescriptive)
    • 1.2
      Analytics Life Cycle — CRISP-DM or similar framework
    • 1.3
      Role of AI in Business Analytics — why AI + analytics is powerful
    • 1.4
      Real-world business use-cases and case studies (from different industries)
  • Module 2: Foundational Mathematics & Statistics
    4
    • 2.1
      Statistics Essentials: descriptive statistics, inferential statistics, probability
    • 2.2
      Hypothesis testing, confidence intervals
    • 2.3
      Regression analysis (linear, logistic)
    • 2.4
      Dimension reduction / feature selection
  • Module 3: Programming for Analytics
    3
    • 3.1
      Introduction to Python (or R) for data analysis
    • 3.2
      Data structures, functions, scripting
    • 3.3
      Working with data: reading/writing files, handling missing data, basic data cleaning
  • Module 4: Data Management & Warehousing
    3
    • 4.1
      Databases: SQL basics, data models
    • 4.2
      ETL (Extract, Transform, Load) processes
    • 4.3
      Data warehouses, marts, OLAP concepts
  • Module 5: Data Analysis & Visualization
    3
    • 5.1
      Exploratory Data Analysis (EDA)
    • 5.2
      Data visualization tools: Matplotlib, Seaborn (if Python), or BI tools like Power BI / Tableau
    • 5.3
      Storytelling with data / dashboard design

AI-Powered Business Analytics Course | Forsk Coding School Jaipur

OffOn

Curriculum

This content is protected, please login and enroll in the course to view this content!
Next Analytics Life Cycle — CRISP-DM or similar framework Next
×

Enter Details

WhatsApp us