Unlock the power of AI in the world of data engineering with this comprehensive learning path. This course series is designed for data professionals who want to harness the transformative potential of artificial intelligence in their work. Whether you're looking to enhance your current role or pivot into AI-driven data engineering, this learning path equips you with the knowledge and skills to thrive in the evolving landscape of data and AI.
-
Build a foundation in AI relevant to data engineering.
-
Harness the power of generative AI in your data workflows.
-
Explore vector databases through practical exercises.
Courses
-
1
AI Fundamentals for Data Professionals1h 7mAI Fundamentals for Data Professionals
By: Sadie St. Lawrence
Discover the fundamental skills, tools, and concepts of AI in this course designed for data professionals.
-
2
Data-Centric AI: Best Practices, Responsible AI, and More2h 50mData-Centric AI: Best Practices, Responsible AI, and More
By: Aishwarya Srinivasan
Learn how AI is shifting from a model-centric approach to a data-centric paradigm, where data serves as the bedrock of all AI endeavors.
-
3
Using AI to Improve Ops for Your Data Organization1h 1mUsing AI to Improve Ops for Your Data Organization
By: Priya Mohan
This course demonstrates how to implement AI strategies in order to improve operations, efficiency, and productivity at data-centric organizations.
-
4
Generative AI for Data Engineering: ChatGPT Power Tips1h 8mGenerative AI for Data Engineering: ChatGPT Power Tips
By: Deepak Goyal
Learn to harness ChatGPT for efficient data engineering, from code generation to workflow optimization in PySpark and Databricks.
-
5
Introduction to AI-Native Vector Databases2h 47mIntroduction to AI-Native Vector Databases
By: Zain Hasan
Learn how data and AI professionals can optimize data systems using AI.
-
6
Vector Databases in Practice: Deep Dive1h 50mVector Databases in Practice: Deep Dive
By: Joon-Pil Hwang
Go beyond the basics of vector databases by building a database and app from scratch, and learn key considerations along the way.
-
7
GraphRAG Essential Training1h 39mGraphRAG Essential Training
By: Dr. Clair Sullivan
Learn how to build robust AI applications by creating knowledge graphs for retrieval-augmented generation (RAG) in Python using LangChain and Neo4j.
-
8
Advanced RAG Applications with Vector Databases1h 18mAdvanced RAG Applications with Vector Databases
By: Yujian Tang
Discover cutting-edge methods to perform retrieval-augmented generation (RAG) with a vector database.
Instructors
Sadie St. Lawrence
CEO @ HMCI |Trained 700,000 + in AI | 2x Founder | Board Member | Keynote Speaker
Aishwarya Srinivasan
Priya Mohan
Manager, Cybersecurity & Tech Risk @ KPMG || Author of Linkedin Learning AI Courses || Forbes Technology Council Member || Speaker || AI Strategist
Deepak Goyal
𝗢𝗻 𝗮 𝗠𝗶𝘀𝘀𝗶𝗼𝗻 𝘁𝗼 𝗺𝗮𝗸𝗲 𝟭𝟬𝟬+ 𝗔𝘇𝘂𝗿𝗲 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗶𝗻 𝗻𝗲𝘅𝘁 𝟰𝟱 𝗗𝗮𝘆𝘀
Zain Hasan
AI builder & teacher | AI/ML @ Together AI | ℕΨ EngSci @ UofT | Lecturer | ex-Vector DBs, Data Scientist, Health Tech Founder
Joon-Pil Hwang
Software Developer | DX, Developer Documentation & Education | Artificial intelligence, database, developer tooling | Python, JS/TS, Golang
Dr. Clair Sullivan
Data science leader, creator of generative AI tools, and keynote speaker | I help companies create innovative, data-driven solutions that generate ROI
Yujian Tang
Guest Lecturer @ Stanford University | CEO @ OSS4AI