Data Analysis — Mastering Data & AI (96 Hours)

Course Overview

96-hour intensive program covering Data Foundations, SQL, Python, Power BI, AI/ML, Agentic AI and real-world projects with full placement support.

The Data Analysis — Mastering Data & AI program is a 96-hour intensive bootcamp designed to take you from absolute beginner to industry-ready data professional. Across 6 progressive phases you will master the complete modern data stack — from foundational concepts and SQL, to Excel, Power BI, Python, Machine Learning, and the latest in Agentic AI.

You will build hands-on projects in Power BI, SQL, Python, and AI Agents, work with real-world datasets, and finish with full career support including visa counseling, resume building, LinkedIn optimization, mock interviews, and placement assistance.

Who This Course Is For: Students & Freshers, Aspiring Data Analysts, Business Analysts, Working Professionals switching to data, and anyone serious about a career in Data & AI.

Every phase combines theory with hands-on lab practice. By the end you will have a complete project portfolio and the confidence to handle real enterprise data challenges and AI workflows.

What you'll learn

Understand the full Data & AI ecosystem — cloud, data centers, APIs, and infrastructure

Apply data security principles and best practices

Master data ingestion, transformation, modeling, and ER diagrams

Work with RDBMS and Non-RDBMS databases (MySQL, Oracle, Databricks)

Perform Data Analysis using Excel — formulas, pivot tables, charts and dashboards

Write complex SQL queries — JOINs, analytics & aggregate functions on real datasets

Build interactive dashboards in Power BI with DAX measures

Perform Exploratory Data Analysis (EDA) using Python and Pandas

Apply statistical concepts — descriptive stats, correlation, hypothesis testing, regression

Understand Machine Learning models — supervised, unsupervised, deep learning

Master Generative AI tools — Claude, Gemini, ChatGPT with hands-on prompting

Build Agentic AI workflows using LangGraph, LangSmith, n8n, RAG and MCP

Complete 4 real-world Lab Projects in Power BI, SQL, Python, and AI Agents

Build a professional Resume and LinkedIn profile tailored for data/AI roles

Get Visa counseling, mock interviews and placement support

Curriculum

Phase 1 — Foundations (5 Hours)

Module 1: Application & Services (3h)

Topic: Software & Hardware (GPUs, Quantum Chips, Processors)

Topic: APIs

Topic: Open Source Technologies

Topic: Cloud Fundamentals & Infrastructure

Topic: Data Centers

Topic: Internet Architecture

Module 2: Domain Understanding (1h)

Topic: Subject Matter Expertise

Module 3: Data Security (1h)

Topic: Data security principles and best practices

Phase 2 — Data Mastery (26 Hours)

Module 4: Data & Storytelling through Data (9h)

Topic: Datasets Preparation — Balanced vs Imbalanced

Topic: Data Ingestion

Topic: Data Democratization

Topic: Data Transformation

Topic: Data Processing

Topic: Data Extraction

Topic: Data Journey

Topic: Data Sources & Destinations

Topic: Data Flow Diagram

Topic: Data Modeling & ER Diagram

Topic: Data Pipelines

Topic: Entity / Attributes

Topic: Data Profiling

Module 5: Databases (1h)

Topic: Types of Databases

Topic: RDBMS vs Non-RDBMS

Topic: MySQL / Oracle

Topic: Databricks

Module 6: Data Analysis Basics (3h)

Topic: Dependent vs Independent Variables

Topic: Descriptive Statistics

Topic: Data Distributions

Topic: Standard Deviation

Topic: Correlational Analysis

Topic: Arithmetic, Geometric & Harmonic Means

Topic: Box Plot and Outliers

Module 7: Data Analysis using Excel (3h)

Topic: Formulas & Functions

Topic: Pivot Tables

Topic: Charts & Dashboards

Module 8: Data Analysis using SQL (9h)

Topic: Tables / Columns / Keys / Relationships

Topic: JOINs

Topic: Analytics Functions

Topic: Aggregate Functions

Topic: Working with Real Datasets

Module 9: File Types (1h)

Topic: JSON

Topic: Spreadsheet Formats

Topic: Text Files & CSV

Phase 3 — Visualization & Analytics (16 Hours)

Module 10: Data Visualization using Power BI (6h)

Topic: Power BI Fundamentals & Workspace

Topic: DAX (Data Analysis Expressions)

Topic: Interactive Dashboards & Reports

Module 11: Data Analysis using Python (3h)

Topic: Exploratory Data Analysis (EDA)

Topic: Outlier Detection & Data Distributions

Topic: Data Quality Check

Topic: Data Scaling

Topic: Multi-collinearity

Topic: Correlation Analysis

Topic: Pandas / DataFrames

Module 12: Advanced Data Analysis Concepts (3h)

Topic: Scatter Plot & Regression

Topic: Hypothesis Testing & Parametric Tests

Module 13: Advanced Data Analysis using SQL (3h)

Topic: Advanced SQL Queries & Optimization

Topic: Real-world Dataset Analysis

Module 14: Databases — Deep Dive (1h)

Topic: RDBMS vs Non-RDBMS (NoSQL)

Topic: Big Data — Hadoop

Topic: MySQL

Topic: Databricks

Phase 4 — AI & Machine Learning (9 Hours)

Module 15: AI vs Gen-AI (3h)

Topic: Traditional AI — Concepts & Applications

Topic: Generative AI — Capabilities & Use Cases

Topic: LLMs: Gemini, ChatGPT, Claude — Hands-on

Module 16: Machine Learning Models (3h)

Topic: Supervised Learning

Topic: Unsupervised Learning

Topic: Deep Learning — CNN & Neural Networks

Topic: Regression, Classification, Clustering

Topic: Dimensionality Reduction

Topic: Association

Module 17: Data Communication (3h)

Topic: API

Topic: WebSocket

Topic: MQTT

Topic: Direct File Transfer

Topic: Data Replication

Phase 5 — Agentic AI (18 Hours)

Module 18: Agentic Workflow & Automation (3h)

Topic: AI Agents — Architecture & Design

Topic: LangSmith

Topic: LangGraph

Topic: N8N

Topic: RAG (Retrieval-Augmented Generation)

Topic: Tokenization

Topic: MCP (Model Context Protocol)

Module 19: AI Tools Awareness & Training (15h)

Topic: Claude — Hands-on Training

Topic: Gemini — Hands-on Training

Topic: Practical AI Tool Workflows

Phase 6 — Projects & Career (22 Hours)

Module 20: Lab Projects (18h)

Topic: Data Visualization Project using Power BI

Topic: Project in SQL

Topic: Project in Python

Topic: Project in Building AI Agents

Module 21: Visa Counseling (1h)

Topic: Guidance on visa processes for international opportunities

Module 22: Resume Building (1h)

Topic: Crafting a data/AI-focused professional resume

Module 23: LinkedIn Profile Creation (1h)

Topic: Building a compelling LinkedIn profile for tech opportunities

Module 24: Placement Support (1h)

Topic: Mock Interviews

Topic: Job Referrals & Employer Connects

Topic: Offer Negotiation Tips