AI Fundamentals for Data Professionals
1h 7mIntermediate2026-06-30
Authors
Sadie St. Lawrence
Course details
If you currently work as a data professional or are looking to land a role in the field, you need to build a foundational understanding of AI concepts, techniques, and tools in order to truly leverage AI and ML effectively. Join instructor Sadie St. Lawrence to learn how to optimize data-driven decision-making processes within your organization by developing in-demand AI and ML skills. Get equipped with essential knowledge for data professionals to stay relevant and competitive in this ever-evolving field, as AI continues to transform the way we work with and understand the value of data. Explore popular tools such as PyTorch, scikit-learn, Keras, XGBoost, and Hugging Face as well as core concepts in data and feature engineering, machine learning, AI ethics, and more.
Skills covered
Data Science FoundationsArtificial Intelligence FoundationsPersonaArtificial Intelligence (AI)Data Science
Concepts
Introduction
- Introduction
Introduction to AI and Machine Learning
- AI and machine learning overview
- Types of machine learning
- Popular AI and ML tools
- AI applications and use cases
Data and Feature Engineering
- Data types and sources
- Exploratory data analysis (EDA)
- Data preprocessing techniques
- Feature engineering
High-Level Machine Learning Techniques
- Supervised learning overview
- Unsupervised learning overview
- Reinforcement learning overview
- Deep learning overview - Part 1
- Deep learning overview - Part 2
Implementation and Future Trends
- Model evaluation and validation
- AI project lifecycle
- AI ethics and bias - Part 1
- AI ethics and bias - Part 2
Conclusion
- Bring it all together