Data Analytics & AI
Become a Data Analyst & AI Developer in 7 Weeks. Master data, build projects, and get industry-ready.
7 Weeks
Duration
Beginner+
Level
Live
Sessions
Course Overview
Everything you will learn and accomplish in a structured 7-week program.
What You'll Learn
- Python for Data Analysis
- NumPy, Pandas & Structured Data
- Data Visualization & EDA
- Statistics & Data Preprocessing
- Machine Learning (Supervised & Unsupervised)
- Generative AI & Chatbot APIs
What You'll Achieve
- 3 Industry-Level Projects
- Data Analytics + Machine Learning Skills
- AI + Chatbot Development
- Portfolio Ready for Jobs & Internships
Why choose this track?
Everything you need to confidently launch a career in Data Analytics & AI.
Continuous Assignments
Doubt clearing sessions
Mock interviews
3 Real-world projects
Course Curriculum
A structured weekly roadmap — from Python fundamentals to data insights and production AI models.
- Understand how companies use data to make decisions
- Role of Data Analyst in industry
- Data Lifecycle (Collection → Cleaning → Analysis → Visualization)
- Tools Overview (Excel, Python, SQL, Tableau)
- Introduction to Generative AI (ChatGPT & AI tools)
- Build strong programming fundamentals
- Variables, Data Types & Type Conversion
- Conditional Logic (if-else, nested conditions)
- Loops (for, while, break/continue)
- Functions (modular & reusable coding)
- Work with structured data like a professional
- NumPy Arrays & Vectorized Operations
- Indexing & Slicing
- Pandas DataFrames & Series
- Data Cleaning (missing values, duplicates)
- Data Manipulation (filtering, sorting)
- Aggregation (groupby, pivot tables)
- Turn data into insights
- Matplotlib (charts & graphs)
- Seaborn (advanced visualization)
- Data Storytelling
- Exploratory Data Analysis (EDA)
- Feature understanding, Correlation analysis & Outlier detection
- 🚀 Project 1: Data Analysis Project (Analyze trends & present insights)
- Build strong analytical foundation
- Mean, Median, Mode, Variance & Standard Deviation
- Probability & Distributions, Normal Distribution
- Data Cleaning & Imputation
- Encoding (Label, One-Hot)
- Feature Scaling (Normalization, Standardization)
- Build predictive models
- ML Concepts (Supervised vs Unsupervised)
- Linear & Logistic Regression, KNN, Decision Trees
- Model Evaluation (Accuracy, Precision, Recall)
- Overfitting (Bias vs Variance)
- K-Means Clustering & PCA (Dimensionality Reduction)
- 🚀 Project 2: Machine Learning Model (Build & train prediction system)
- Work with modern AI tools
- LLM Basics (How ChatGPT works)
- Prompt Engineering (Zero-shot, Few-shot, Role prompting)
- AI Workflows (Automation & productivity)
- Chatbot Development (API-based AI apps)
- AI Content Generation
- 🚀 Final Project: AI Chatbot Application (Integrate APIs + prompt engineering)
- 🔧 Bonus: Portfolio & Industry Tools (Git & GitHub, Project deployment)
Data Analytics & AI7 Weeks
Starting at ₹4,999