🤖 AI & Machine Learning

Artificial Intelligence
& Machine Learning

A structured 7-phase program taking you from Python fundamentals through data analysis, classical ML, deep learning, NLP, and model deployment — culminating in 5 real-world projects including a live deployed ML web application.

7
Phases
5
Projects
Live+
Recorded
0
Prior Exp. Needed
📥 Download Syllabus
Beginner–Advanced
AI & Machine Learning
₹25,000
🐍
Python to Deep Learning Coverage
📺
Live + On-Demand Video Content
🏆
5 Real-World Projects
🚀
Model Deployment with Flask/FastAPI
📄
Completion Certificate
💼
Placement Assistance
🔄
Lifetime Access to Content

What You'll Learn

✓
Python programming from scratch — OOP, data structures, file handling
✓
Data analysis with NumPy, Pandas & data visualisation
✓
Supervised ML — Regression, KNN, Decision Trees, Random Forest, SVM
✓
Unsupervised ML — K-Means, Hierarchical Clustering, DBSCAN, PCA
✓
Deep Learning — Neural Networks, CNNs, TensorFlow & Keras
✓
NLP — Tokenization, TF-IDF, Sentiment Analysis, BERT & GPT
✓
Transformers, Prompt Engineering & LLM usage
✓
Model deployment with Flask, FastAPI & Streamlit

Tools & Technologies

🐍 Python
📓 Jupyter Notebook
🔢 NumPy
🐼 Pandas
📊 Matplotlib
🎨 Seaborn
🤖 Scikit-Learn
🧠 TensorFlow
⚡ Keras
🔥 PyTorch (concept)
🗣️ NLTK / spaCy
🤗 Hugging Face / BERT
🌐 Flask / FastAPI
📡 Streamlit
🔗 OpenAI / GPT

7-Phase Curriculum

Phase 1Python Programming
▼
Variables and Data Types
Operators, Conditional Statements & Loops
Functions
Lists, Tuples, Sets, Dictionaries
File Handling and Exception Handling
Object-Oriented Programming (OOP)
Working with Libraries and Jupyter Notebook
Phase 2Data Analysis & Visualization
▼
NumPy Arrays and Operations
Pandas DataFrames and Data Cleaning
Handling Missing Values
Data Preprocessing
Matplotlib and Seaborn
Data Interpretation
Phase 3Machine Learning
▼
Introduction to AI, ML and Deep Learning
Machine Learning Workflow
Supervised Learning: Linear and Logistic Regression
KNN, Decision Trees, Random Forest, SVM
Model Evaluation Metrics
Unsupervised Learning: K-Means, Hierarchical Clustering, DBSCAN, PCA
Phase 4Deep Learning
▼
Neural Networks and Activation Functions
Loss Functions and Backpropagation (Concept)
TensorFlow / Keras Implementation
Convolutional Neural Networks (CNN)
Image Classification and Transfer Learning
Phase 5Natural Language Processing
▼
Text Preprocessing and Tokenization
TF-IDF and Text Classification
Sentiment Analysis
Introduction to Transformers
BERT and GPT (Concept and Usage)
Prompt Engineering
Phase 6Model Deployment
▼
Flask / FastAPI for serving ML models
Streamlit Applications
Building ML Web Applications
API Integration
Model Hosting Basics
Phase 7Capstone Projects
▼
House Price Prediction
Loan Approval System
Customer Segmentation
Spam Detection
End-to-End ML Application with Deployment
🏆 Real-World Projects

Apply your skills across 5 end-to-end projects covering supervised learning, unsupervised clustering, NLP, and a fully deployed ML web application — all portfolio-ready.

Project 1
🏠 House Price Prediction
Regression model to predict real estate prices
Project 2
💳 Loan Approval System
Classification model for automated loan decisions
Project 3
👥 Customer Segmentation
Clustering customers using unsupervised ML
Project 4
📧 Spam Detection
NLP-powered email/SMS spam classifier
Capstone Project
🚀 End-to-End ML App
Full pipeline — train, evaluate & deploy with Flask/Streamlit
Capstone Pipeline
🐍 Python
→
🐼 Pandas / NumPy
→
🤖 Scikit-Learn
→
🧠 TensorFlow
→
🌐 Flask / Streamlit
→
☁️ Deployed App
📋 Prerequisites
No prior programming or AI experience needed
Basic computer literacy & curiosity
A laptop/PC with internet connection
Willingness to practice daily exercises
🎯 Career Outcomes
✓Machine Learning Engineer
✓Data Scientist
✓AI Engineer
✓NLP Engineer
✓Data Analyst
✓ML Deployment / MLOps Engineer
🏭 Key Sectors Hiring
→Technology & Software
→Finance & FinTech
→Healthcare & MedTech
→E-Commerce & Retail
→Data Science & Analytics
→Startups & AI Incubators
💬 Chat or Call us!
Chat on WhatsApp
+91 9187135171