Generative AI

Embark on a transformative journey with our GenAI Product Development course, designed to equip you with the knowledge and skills necessary to design, build, deploy, and maintain cutting-edge Generative AI applications. This course is tailored for individuals with foundational coding and product experience, enhancing your expertise with a state-of-the-art, AI-augmented learning experience. Prepare to dive deep into the realm of Generative AI and emerge ready to create innovative solutions that make a significant impact.

Course Starts

March 31st, 2025

Estimated Time

8 Weeks

at 6 to 8 hours per week

Format

Online, self-paced

Complemented with live support from AI and our instructors

Price

USD 999 USD 499

Discounted for a limited time

Audience
Who is this course for?
Innovative Tech Enthusiasts
Programmers and technical creators eager to develop cutting-edge products powered by Large Language Models, seeking to harness the full potential of AI in their innovative solutions.
Visionary Product Strategists
Technical Product Managers who lead their teams and product development, aiming to gain a deep understanding of Large Language Models to solve complex customer needs and drive innovation.
Objectives
What will you get out of this course?

An understanding LLMs and their architecture, designing and applying use cases, optimizing performance, ensuring safety and ethical usage, and evaluating their effectiveness in real-world scenarios.

Understand what Large Language Models (LLMs) are, how they work, including their foundational concepts, the intricacies of the training process, how they leverage transformer architectures, and the challenges associated with scaling.

Design use cases that are a good fit for applying LLM solutions. Apply principle from technical design and product design to navigate the spectrum of use cases that are feasible using what LLMs are capable of, yet simpler algorithms or heuristics would be ineffective.

Apply various LLM techniques tailored to specific needs, including prompt engineering, in-context learning, zero-shot, single-shot, and few-shot learning, along with chain-of-thought reasoning.

Optimize LLM performance through strategic methods such as LLM Fine-Tuning, extending LLM capabilities using external tools and APIs, grounding their memory with Retrieval-Augmented Generation (RAG), and unleashing their potential via Agentic Planning workflows.

Mitigate risks by focusing on the critical aspects of safety and alignment in LLMs to ensure ethical and responsible usage.

Evaluate LLMs through benchmarking and metrics, understanding their capabilities and limitations in real-world scenarios. Continuously monitor and maintain LLM through observability to ensure effective performance in various environments.

Content
What will the course cover?

We took every care to select and organize the course content to maximize value, empowerment, and ease of comprehension for our learners.

Questions
Frequently asked questions
General
Content
Payment

Have other questions? Please drop us a line at team@optima.io.

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