From Python basics to transformers with PyTorch! Master deep learning, CNNs, and attention. Build Generative AI Project
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Master Python, PyTorch & Transformers: From Basics to Advanced AI Projects
Course Highlights:
Master Python & Core Libraries
Learn Python basics (syntax, data structures, OOP).
Manipulate data with Pandas, crunch numbers with NumPy, and visualize insights with Matplotlib.
Build Machine Learning Foundations
Code ANNs, linear/logistic regression from scratch in Python (no frameworks!).
Reimplement models using PyTorch to leverage tensor operations and autograd.
Dive into Transformers & Modern AI
Decode the Transformer paper (attention mechanisms, positional encoding, self-attention).
Build a Transformer from scratch in PyTorch—layer by layer!
Industry-Ready Projects
Project 1: Build a Transformer Model End-to-End
Train it on real data for tasks like text generation or translation.
Project 2: RAG (Retrieval-Augmented Generation) Agent with DeepSeek
Integrate retrieval models + transformers to create an AI agent that answers questions using external knowledge.
Handle data pipelines, fine-tuning, and deployment.
Why This Course Stands Out?
Zero to Advanced: Start with Python basics, end with cutting-edge AI.
Code Without Frameworks First: Deepen understanding before using PyTorch shortcuts.
Paper-to-Practice: Implement the Transformer architecture exactly as described in the seminal paper.
Portfolio Boost: Showcase your RAG agent and Transformer projects to employers.
Perfect For:
Aspiring AI/ML engineers, data scientists, or developers.
Learners who want hands-on projects (not just theory!).
Anyone aiming to crack NLP roles or build LLM-powered apps.
You’ll Leave With:
Fluency in Python, PyTorch, and transformer theory.
A deployed RAG agent project + full Transformer implementation.
Confidence to tackle real-world AI challenges.
Enroll Now – Transform Code into Intelligent Systems!