#	Class 1-2	Python basics	Python Data types
1	Introduction to Python	Modules, pip, comments	Variables,Data Type, Type Casting,
#	Class 3-4	Conditional Expressions	Loops
2	if, elif, else statements	if-else ladder	For loop, While loop

#	Class 5-6	Libraries for AI	Libraries for Data manipulation
1		Pytorch	Numpy, Pandas
#	Class 7-8	Data Visualization	Data Graphing
2		Matplotlib	Plotting graphs, bar chart, histogram for data representation

#	Class 9-10	Introduction to GenAI	Introduction to LLMs
1		Use GenAI models	Introduction to pipeline function
#	Class 11-12	OpenAI models	Gemini models
2	Write Code of Open Source models	Use GPT-3, GPT-4o mini etc	Gemini 1.5 Flash

#	Class 13-14	Prompt Engineering	Introduction to HuggingFace
1		Use models and pipeline for prompt engineering	Choose best models for specific task
#	Class 15-16	NLP(Natural language processing)	Computer Vision
2	Advanced NLP and CV	Use OpenAI for Chatbot and Image generation	Use Gemini for Image and Video Classification

#	Class 17-18	Machine Learning (ML)	ML with Transformers
1	Introduction to Transformers Library	Use Transformers for machine learning	NLP, Computer Vision, Audio, Multimodal
#	Class 19-20	Sentiment Analysis	Table-QA
2		Analyzing digital text, the emotional tone of the message is positive or negative	Ask Question about CSV file from database

#	Class 21-22	Text-Generation	Image-To-Text
1	Transformers for NLP	Use conversational model	Use Image classification model
#	Class 23-24	Text-To-Image	Audio Classification
2	Transformers for CV and Audio	Use Image generator model	Use audio Classification model

#	Class 25-26	Unsupervised Learning	Supervised Learning
1		uses machine learning(ML) algorithms create and analyze datasets	machine learning that uses labeled datasets to train algorithms to predict output
#	Class 27-28	Introduction to Datasets	Fine-tuning
2	Train Models	HuggingFace dataset	Train models through huggingface datasets

#	Class 29-30	Train NLP datasets	Train Computer Vision datasets
1	Data Collection	Collecting data for NLP	Collecting data for Computer Vision
#	Class 31-32	Train NLP Models	Train Computer Vision Models
2	Traning models	AutoTokenizer, AutoModel, Pytorch	Using Diffusers library for traing CV Models

#	Class 33-34	Introduction to Deep learning	Deep learnig for NLP
1		Train models with high level of programming	Hands on practice for NLP
#	Class 35-36	DL for computer Vision	Train models on large datasets
2		Hands on practice for Computer Vision	train models with multiple datasets

#	Class 37-38	Chatbot with custom datasets	Project Face-Recognizer
1		hands on project chatbot	hands on project face recognizer
#	Class 39-40	project incorporating	#
2	Final Project Presentation	Students present a final project incorporating all the advanced AI concepts learned in	#

#	Class 41-42	Introduction to Reinforcement Learning	RL with HuggingFace
1		learn about Agent, State, Environment, Reward, Action	Learn huggingface libraries Stable Baselines3, RL Baselines3 Zoo, Sample Factory and CleanRL
#	Class 43-44	Use Stable Baselines3 library	Q-learning
2		Project Presentation	implement our first RL agent from scratch

#	Class 45-46	Train Game Agents	Use Agent against other student's Agent
1		Train Huggy the Dog	Hands on project
#	Class 47-48	Project incorporating	#
2		Final Project Presentation	Students present a final project incorporating all the advanced AI concepts learned in

#	Class 49-50	Maths for AI	Introduction to Calculus in AI
1		Introduction to weight and biases	learn how neural network works
#	Class 51-52	Introduction to Linear Algebra in AI	#
2		Clustering, data fitting, classification, validation, and feature engineering	#

#	Class 53-54	Introduction to Neural Network	#
1		Create Basic structure of neural network	#
#	Class 55-56	Create LLMs from scratch	#
2		Create LLMs through neural network	#

#	Class 57-58	Introduction to Robotics	Interfacing Aurduino With python
1		Learn about Aurduino and it's Sensors	Write python code for interacting sensors
#	Class 59-60	LLMs with Aurduino	#
2		Use large language modules with Aurduino	#

#	Class 61-62	Basic Autonomous Robotics	Decision-Making algorithms
1		Intracting Computer Vision, Audio, NLP with aurdino	Train the robot to make the right decision depending on the situation.
#	Class 63-64	project incorporating	#
2	Final Project Presentation	Students present a final project incorporating all the advanced AI concepts learned in	#