🤖 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
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
Enroll Now

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

Frequently Asked Questions

Who can learn this course?
Students who have completed graduation, working professionals, data enthusiasts, and career switchers can enroll in this program.
What skills and tools will I learn in this program?
You will learn data handling, machine learning techniques, deep learning, AI concepts, and model deployment.

Tools: Programming languages, development tools, machine learning libraries, and data visualization tools.
What is the average salary of an AI & ML specialist in India?
Entry-level AI/ML professionals can earn around ₹5–10 LPA. With 2–5 years of experience, salaries range between ₹10–20 LPA. Senior roles like AI Engineer or ML Architect can earn ₹25–50 LPA or more depending on expertise and company.
Can non-technical students learn Artificial Intelligence & Machine Learning?
Yes, non-technical students can learn AI and ML even without a programming background. The course typically starts with basics and gradually moves to advanced concepts.
Is AI & ML a good career choice for freshers?
Yes, AI & ML is an excellent career choice for freshers, especially if you focus on building strong fundamentals, hands-on projects, and practical skills.
Is certification important for AI & ML?
Certification is helpful but not mandatory. Employers value practical skills, real-world projects, and problem-solving ability more than just certificates.
Does this course include placement support?
Yes, we provide placement assistance and help you prepare for interviews with resume building, mock interviews, and career guidance.
What is the future scope of Artificial Intelligence & Machine Learning?
The future of AI & ML is extremely promising. These technologies are transforming industries like healthcare, finance, e-commerce, and automation. With increasing demand for AI-driven solutions, career opportunities will continue to grow rapidly worldwide.