Python Refresher with AI is the first step in your AI journey, building the technical foundation for advanced applications. This course introduces core programming concepts, including data types, operators, control structures, functions, loops, and error handling. By understanding these fundamentals, you'll take a crucial step toward tackling other courses in the Professional Certificate in AI and Machine Learning program.

Gain core data science skills with Python. This course covers data prep, model building, and evaluation using tools like NumPy and pandas. Master statistics concepts—central tendency, dispersion, skewness, and hypothesis testing (Z-test, T-test, ANOVA). Build visuals with Matplotlib, Seaborn, Plotly, and Bokeh. Develop end-to-end data analysis and wrangling expertise using Python libraries and techniques.

Learn the machine learning pipeline. Focus on supervised learning with regression and classification, explore unsupervised learning and clustering, and understand overfitting and underfitting. Dive into ensemble methods like bagging, boosting, and stacking. Gain hands-on experience with PyTorch and explore frameworks like TensorFlow and Keras to build a recommendation engine.

This course distinguishes deep learning fundamentals and applications from machine learning. Learn neural networks, forward/backward propagation, TensorFlow 2, Keras, and PyTorch. Explore hyperparameter tuning, model interpretability, dropout, early stopping, CNNs for object detection, transfer learning, RNNs, and autoencoders.

This course explores machine learning types and generative AI algorithms, including chatbots, LLMs, and AI-based image/video generation. Learn about transformer algorithms, GANs, VAEs, ChatGPT models, and neural networks and discover appropriate tools for various AI tasks.

This AI ML course covers the fundamentals, evolution, and applications of generative AI across text, image, audio, video, code, and more. Learn about GPT, DALL-E, Stable Diffusion, and Synthesia. Explore use cases in text and code generation, compare generative and discriminative AI, and apply GenAI tools like Hugging Face, TensorFlow, and PyTorch to solve data science challenges.

This course explores foundational models and pre-trained AI platforms for generating text, images, and code. Learn about IBM watsonx, Hugging Face, IBM Granite, GPT, FLAN, and Llama. Understand deep learning, large language models, and generative AI use cases through hands-on projects and quizzes.

The capstone project lets you apply your AI knowledge to real-world challenges. With mentor guidance, demonstrate your technical skills through a practical, industry-based project. Gain hands-on experience and build a portfolio-worthy piece to showcase to potential employers.