About the Course
The exam covers the following objectives:
- Recall the history and evolution of Large Language Models (Remembering).
- Compare the features of different Large Language Models (Understanding).
- Evaluate the strengths, limitations, and business applications of Large Language Models (Evaluating).
- Construct various types of prompts (Creating).
- Conduct hands-on experimentation with basic use cases (Applying).
- Interpret the importance and usage of model parameters for tuning and training (Understanding).
- Adjust tone, length, and formatting in prompts to achieve desired results (Applying).
- Analyze the influence of iterative refining in prompt effectiveness (Analyzing).
- Create effective prompts using learned techniques (Creating).
- Apply advanced prompting techniques such as zero-shot, few-shot, and role-playing (Applying).
- Understand large data interactions, variable inputs, and the concept of Mega Prompting (Understanding).
- Develop strategies for more nuanced responses and large data interactions with AI (Creating).
- Demonstrate the application of learned concepts to real-world business scenarios (Applying).
- Evaluate how LLMs can enhance productivity and power communication (Evaluating).
- Analyze the role of LLMs in sparking creativity, initiating projects, aiding in personal and professional growth, and streamlining workflows (Analyzing).
- Identify the ethical considerations and future prospects in AI (Remembering).
Delivery Type