25 Courses on Artificial Intelligence by IBM
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Generative AI and LLMs: Architecture and Data Preparation
Differentiate between generative AI architectures and models, such as RNNs, Transformers, VAEs, GANs, and Diffusion Models.
Generative AI for Executives and Business Leaders
Apply generative AI to key use cases like customer service and application modernization.
Generative AI Language Modeling with Transformers
Implement positional encoding, masking, attention mechanism, document classification, and create LLMs like GPT and BERT.
Generative AI: Boost Your Cybersecurity Career
Assess the use of generative AI in cybersecurity against threats, like phishing and malware, and understand potential NLP-based attack techniques.
Machine Learning with Python
Compare and contrast linear classification methods including multiclass prediction, support vector machines, and logistic regression.
AI Workflow: Machine Learning, Visual Recognition and NLP
Covers the next stage of the workflow, setting up models and their associated data pipelines for a hypothetical streaming media company.
Machine Learning Introduction for Everyone
Differentiate between supervised and unsupervised machine learning.
Generative AI: Prompt Engineering Basics
Explore commonly used tools for prompt engineering to aid with prompt engineering.
AI Workflow: Data Analysis and Hypothesis Testing
In this course you will begin your work for a hypothetical streaming media company by doing exploratory data analysis (EDA).
Data Analysis with Python
Develop Python code for cleaning and preparing data for analysis - including handling missing values, formatting, normalizing, and binning data.