AI Fundamentals for Data Professionals

1h 7mIntermediate2023-12-15

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

0. Introduction

01 - Introduction

1. Introduction to AI and Machine Learning

02 - AI and machine learning overview
03 - Types of machine learning
04 - Popular AI and ML tools
05 - AI applications and use cases

2. Data and Feature Engineering

06 - Data types and sources
07 - Exploratory data analysis (EDA)
08 - Data preprocessing techniques
09 - Feature engineering

3. High-Level Machine Learning Techniques

10 - Supervised learning overview
11 - Unsupervised learning overview
12 - Reinforcement learning overview
13 - Deep learning overview - Part 1
14 - Deep learning overview - Part 2

4. Implementation and Future Trends

15 - Model evaluation and validation
16 - AI project lifecycle
17 - AI ethics and bias - Part 1
18 - AI ethics and bias - Part 2

Conclusion

19 - Bring it all together