Curriculum
5 Sections
17 Lessons
10 Weeks
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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
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