What You will learn in this program ?
30 Days Challenge Application Based Learning + Bonuses
Day 1: Introduction to AI, ML, and DL
Day 2: Python for Machine Learning
Day 3: Linear Algebra and Calculus for ML
Day 4: Supervised and Unsupervised Learning
Day 5: Model Evaluation and Cross-Validation
Day 6: Introduction to Neural Networks
Day 7: Convolutional Neural Networks (CNNs)
Day 8: Recurrent Neural Networks (RNNs)
Day 9: LSTM and GRU Networks
Day 10: Autoencoders and Variational Autoencoders (VAEs)
Day 11: Introduction to GANs
Day 12: Deep Convolutional GAN (DCGAN)
Day 13: Wasserstein GAN (WGAN)
Day 14 - Conditional GANs (cGANs)
Day 15 - CycleGAN
Day 16 - Introduction to Language Models
Day 17 - Transformer Architecture
Day 18 - Hugging Face and Pre-trained Models
Day 19 - Text Summarization and Question Answering
Day 20 - Machine Translation
Day 21- Introduction to Retrieval-Augmented Generation (RAG)
Day 22 -LangChain for LLMs
Day 23 - Few-shot and Zero-shot Learning
Day 24 - Prompt Engineering
Day 25 - Advanced Fine Tuning Techinques
Day 26 - Generative Models for Healthcare Applications
Day 27 - Generative Models for Scientific Applications
Day 28 - Generative Models for Art and Design
Day 29 - Generative Models for Audio and Time Series
Day 30 - Real-world - Final Project
