Online Training - Data Science & AI Live

Online Live Batch 2025

Decode The
DATA UNIVERSE

Master Data Science & AI from home. Live sessions on Python, Machine Learning models, and predictive analytics projects.

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Algorithms

Intelligence

Insights

Analysis.ipynb (Python 3)

Kernel Ready

In [1]:

Real-time Prediction Accuracy

Epoch 1Epoch 5Epoch 10Epoch 15Epoch 20

[ LIVE CURRICULUM ]

Detailed Topic Breakdown

From Data Cleaning to Model Deployment. Learn the complete pipeline of a Data Scientist.

Module 1

Python & Stats

Core Python programming and Statistical mathematics for Data Science.

Week 1 (Day 1-7)

Part A: Python for Data

Python Env Setup (Anaconda/Jupyter)
Variables, Lists, Dictionaries
Functions & Lambda Expressions
NumPy Arrays & Matrix Operations
Pandas DataFrames Basics
File Handling (CSV, JSON, Excel)
Data Cleaning Techniques
Handling Missing Values
Data Transformation
Automating Data Scripts

Part B: Statistics

Descriptive Statistics (Mean, Median)
Probability Distributions
Standard Deviation & Variance
Hypothesis Testing (T-test, Z-test)
Correlation vs Causation
Central Limit Theorem
A/B Testing Concepts
Data Visualization (Matplotlib)
Seaborn for Statistical Plots
Exploratory Data Analysis (EDA)

Module 2

Machine Learning

Supervised and Unsupervised Learning algorithms using Scikit-Learn.

Week 2 (Day 8-14)

Part A: Supervised ML

Linear Regression (Simple/Multiple)
Logistic Regression
Decision Trees & Random Forest
Support Vector Machines (SVM)
K-Nearest Neighbors (KNN)
Model Evaluation (Accuracy, Precision)
Confusion Matrix & ROC Curve
Cross-Validation Techniques
Hyperparameter Tuning
Project: House Price Prediction

Part B: Unsupervised ML

K-Means Clustering
Hierarchical Clustering
Principal Component Analysis (PCA)
Dimensionality Reduction
Association Rule Mining
Recommendation Systems Basics
Feature Engineering
Handling Imbalanced Data
Ensemble Methods (Boosting)
Project: Customer Segmentation

Module 3

Deep Learning & DB

Neural Networks, TensorFlow/Keras, and SQL for Data Science.

Week 3 (Day 15-21)

Part A: Neural Networks

Intro to Artificial Neural Networks (ANN)
Perceptrons & Activation Functions
Forward & Backward Propagation
TensorFlow & Keras Basics
Building Sequential Models
Convolutional Neural Networks (CNN)
Image Classification Project
Overfitting & Dropout
Natural Language Processing (NLP) Intro
Sentiment Analysis Basics

Part B: SQL & Database

SQL vs NoSQL
RDBMS Concepts (MySQL)
SELECT, WHERE, JOINs
Group By & Aggregation
Subqueries & Window Functions
Connecting Python to SQL
Data Extraction from DB
Database Normalization
Table Operations
ETL (Extract, Transform, Load) Intro

Module 4

BI & Capstone

Data Visualization with Tableau/PowerBI and Final Project.

Week 4 (Day 22-28)

Part A: Business Intelligence

Tableau Interface & Basics
Connecting Data Sources
Dimensions vs Measures
Creating Charts & Graphs
Interactive Dashboards
PowerBI Fundamentals
DAX Basics (PowerBI)
Storytelling with Data
Exporting Reports
Data Governance

Part B: Capstone

End-to-End ML Pipeline
Project: Titanic Survival Prediction
Project: Sales Forecasting
Model Deployment (Flask/Streamlit)
Git & GitHub for Data Science
Resume Building
Mock Interviews
Kaggle Competitions
Final Presentation
Certification

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Access the complete 30+ page Training Report, Datasets, Notebooks, and Slides.

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Data Science & AI Live

Detailed Topic Breakdown

Python & Stats

Part A: Python for Data

Part B: Statistics

Machine Learning

Part A: Supervised ML

Part B: Unsupervised ML

Deep Learning & DB

Part A: Neural Networks

Part B: SQL & Database

BI & Capstone

Part A: Business Intelligence

Part B: Capstone

Download Data Resources

DS Training Report

Datasets

Project Slides