The AI and Deep Learning with Python course is designed to help learners build a strong practical foundation in artificial intelligence and deep learning. This hands-on course focuses on how neural networks are built, trained, evaluated, improved, and used to solve real-world problems using Python, scikit-learn, Keras, and TensorFlow.
You will learn how to build deep learning models for classification and regression and work with text using Natural Language Processing (NLP). The course also introduces modern AI concepts such as transformers and Large Language Models (LLMs), helping you understand how modern language-based AI systems have evolved.
You will also learn how to evaluate and improve neural network performance, save trained models, make predictions on new data, and understand how models can be used in real applications. The course concludes with an end-to-end capstone project where you apply the full deep learning workflow to a real-world business problem.
By the end of the course, you will be able to:
- Build and train neural networks using Keras and TensorFlow
- Develop deep learning models for classification and regression
- Work with structured data, text, and image data
- Apply NLP techniques and build text classification models
- Evaluate, improve, save, and reuse trained deep learning models
- Understand the basic concepts behind transformers and Large Language Models (LLMs)
- Complete an end-to-end AI and deep learning project
- Prepare for more advanced AI, Generative AI, and deep learning development