Deep Learning with Python From Fundamentals to Advanced AI

 

This course is designed to provide a comprehensive understanding of deep learning using Python. It covers fundamental concepts, essential frameworks like TensorFlow and PyTorch, and practical applications in real-world AI projects. By the end of the course, you will have hands-on experience building deep neural networks, optimizing models, and implementing cutting-edge AI techniques.

Who Should Take This Course?
Aspiring Data Scientists & AI Engineers
Software Developers interested in AI
Machine Learning Practitioners
Researchers and Academics
Anyone with a basic understanding of Python and Machine Learning
Course Modules & Curriculum
Module 1: Introduction to Deep Learning
What is Deep Learning?
Difference Between Machine Learning & Deep Learning
Applications of Deep Learning
Setting Up Python Environment (Jupyter, Colab)
Module 2: Python for Deep Learning
NumPy, Pandas, and Matplotlib Basics
Data Preprocessing Techniques
Feature Engineering for Deep Learning
Module 3: Neural Networks Basics
Understanding Perceptrons & Artificial Neural Networks (ANN)
Forward & Backpropagation
Activation Functions (ReLU, Sigmoid, Tanh, Softmax)
Module 4: Deep Learning Frameworks
Introduction to TensorFlow & PyTorch
Building First Neural Network with Keras
Comparing TensorFlow vs PyTorch
Module 5: Convolutional Neural Networks (CNNs)
Introduction to CNNs & Their Importance
Architecture of CNN (Convolution, Pooling, Flattening, Fully Connected)
Implementing CNN with TensorFlow/Keras
Real-world Applications: Image Classification & Object Detection
Module 6: Recurrent Neural Networks (RNNs) & LSTMs
Understanding Sequential Data
Basics of RNN, LSTM, and GRU
Implementing RNNs for Time-Series Forecasting & NLP Tasks
Module 7: Advanced Deep Learning Architectures
Autoencoders for Feature Learning & Anomaly Detection
Generative Adversarial Networks (GANs)
Transfer Learning with Pre-trained Models (VGG, ResNet, Inception)
Module 8: Natural Language Processing with Deep Learning
Word Embeddings (Word2Vec, GloVe, BERT)
Sentiment Analysis Using LSTMs
Chatbot Development with Deep Learning
Module 9: Model Optimization & Deployment
Hyperparameter Tuning & Model Optimization
Using Google Colab for Large Model Training
Deploying Deep Learning Models with Flask & FastAPI
Module 10: Capstone Project & Certification
Hands-on Deep Learning Project
Model Evaluation & Improvement
Resume Building & Career Guidance
Certification of Completion

Course Highlights
✅ Hands-on Coding with Real-World Projects
✅ Interactive Learning with Industry Experts
✅ Access to Course Materials & Recorded Sessions
✅ Certification Upon Completion
✅ Job Assistance & Career Support