Course Modules
Our Course Modules
All lectures are in Hindi with practical examples.
1
What is Artificial Intelligence?
Basics of AI explained
2
AI vs ML vs DL vs DS
Key differences overview
3
Trends in AI 2025
Latest AI technologies today
4
AI Career Roles
Jobs in AI field
5
Roadmap to AI Engineer
Stepwise path to learn
6
Python Basics
Syntax, loops, data types
7
OOP in Python
Classes and objects usage
8
Python Libraries Overview
NumPy, Pandas, Matplotlib intro
9
Data Handling in Python
Working with datasets easily
10
Python Visualization Tools
Matplotlib, Seaborn, Plotly basics
11
Linear Algebra Fundamentals
Vectors and matrices basics
12
Probability Concepts
Mean, variance, distribution basics
13
Statistics in AI
Central tendency and spread
14
Calculus for AI
Gradients and derivatives explained
15
Gradient Descent Method
Optimization algorithm overview
16
Machine Learning Lifecycle
End-to-end ML steps
17
Supervised Learning Types
Regression and classification explained
18
Unsupervised Learning
Clustering and dimensionality reduction
19
Feature Engineering Basics
Extracting useful data features
20
Model Evaluation Metrics
Accuracy, F1-score, recall
21
Intro to Deep Learning
Neural networks foundation
22
ANN Architecture
Input, hidden, output layers
23
Activation Functions
ReLU, Sigmoid, Softmax intro
24
Loss Functions Overview
Used for model training
25
TensorFlow and Keras Basics
Frameworks for deep learning
26
Train Model with GPU
Hardware for faster training
27
Natural Language Basics
Understanding text data
28
Text Preprocessing Steps
Tokenize, stopwords, lemmatization
29
Bag of Words TF-IDF
Convert text to numbers
30
Word Embeddings
Word2Vec, GloVe concepts
31
Sentiment Analysis
Classify text emotions
32
Transformers & BERT
Modern NLP deep models
33
Computer Vision Basics
Image data and channels
34
Image Preprocessing
Resize, normalize, enhance
35
CNN Architecture Overview
Convolutions and pooling explained
36
Face Detection
Identify faces in images
37
YOLO Object Detection
Real-time detection intro
38
Generative AI Introduction
Create new data content
39
LLM Working Overview
Transformers and tokens used
40
Using ChatGPT & Gemini
Prompt-based model access
41
Prompt Engineering Basics
Design effective AI prompts
42
LangChain Framework
Build smart AI agents
43
Gradio UI Basics
Deploy AI apps simply
44
MLOps Introduction
Manage ML model lifecycle
45
Git and Version Control
Track project history
46
Docker for ML
Run models in containers
47
Streamlit Dashboards
Create interactive web apps
48
Model Monitoring MLflow
Track and manage models
49
Build AI Portfolio
Showcase your AI skills
50
LinkedIn for AI
Professional branding tips
51
GitHub Project Tips
Structure projects effectively
52
Freelancing in AI
Get real projects online
53
Mock Interviews
Prepare for AI jobs
54
AI Ethics Basics
Bias, fairness, safety
55
AI Research Papers
Structure and write papers
56
Free AI Resources
Tools, datasets, platforms
57
Hindi AI Content
Strategy for YouTube learning
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