Demystifying Generative AI & Large Language Models: Business Applications & Use Cases

Actionable Analytics
This series explores the integration and usage of Generative AI (GAI) and Large Language Models (LLMs) as it relates to working with popular data analytics tools, such as: Excel, SQL and Python. GAI and LLMs have exploded on the business scene yielding a proliferation of use cases on how they can streamline processes, automate tasks, and support data-driven decision making. However, for someone to benefit from GAI and LLMs they first must understand how they work in the context of a specific data analytics tool.

Demystifying Generative AI & Large Language Models: Business Applications & Use Cases

Actionable Analytics
This series explores the integration and usage of Generative AI (GAI) and Large Language Models (LLMs) as it relates to working with popular data analytics tools, such as: Excel, SQL and Python. GAI and LLMs have exploded on the business scene yielding a proliferation of use cases on how they can streamline processes, automate tasks, and support data-driven decision making. However, for someone to benefit from GAI and LLMs they first must understand how they work in the context of a specific data analytics tool.

prerequisites

Successful completion of

duration

Full day or
two half-days

Virtual or in-person

certification

afterskills AI practitioner

Awarded upon completion

course description_

The curriculum starts by providing a foundational understanding of Generative AI (GAI) and Large Language Models (LLMs) concepts, demonstrating their potential in data analytics before moving onto engaging exercises. The curriculum next delves into GAI and LLMs and how it relates to a given tool. Participants will master the art of translating GAI and LLMs responses into actionable insights elevating their ability to solve multifaceted problems and debug complex code.

Upon completion, participants will possess a comprehensive skill set ranging from crafting prompts to seamlessly generating insight.

agenda

Topic 1: Introduction to GAI and LLMs
Topic 2: Overview of GAI and LLMs technologies
Topic 3: Crafting prompts for data analytics
Topic 4: Integrating GAI/LLMs with analytics tools
Topic 5: Automating code with GAI/LLMs
Topic 6: Debugging/optimizing code with GAI/LLMs
Topic 7: Applying GAI/LLMs to business problems
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