AI Fundamentals for Data Professionals

سرفصل های دوره

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.

01 - Introduction

01 - Introduction

02 - 1. Introduction to AI and Machine Learning

01 - AI and machine learning overview

02 - Types of machine learning

03 - Popular AI and ML tools

04 - AI applications and use cases

03 - 2. Data and Feature Engineering

01 - Data types and sources

02 - Exploratory data analysis (EDA)

03 - Data preprocessing techniques

04 - Feature engineering

04 - 3. High-Level Machine Learning Techniques

01 - Supervised learning overview

02 - Unsupervised learning overview

03 - Reinforcement learning overview

04 - Deep learning overview Part 1

05 - Deep learning overview Part 2

05 - 4. Implementation and Future Trends

01 - Model evaluation and validation

02 - AI project lifecycle

03 - AI ethics and bias Part 1

04 - AI ethics and bias Part 2

06 - Conclusion

01 - Bring it all together

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تولید کننده: LinkedIn Learning (Lynda)