Applied GenAI Specialisation Learning Path
Who will benefit
This learning path, provided by our partner Simplilearn, is aimed at working professionals from a variety of industries and backgrounds. It will specifically benefit anyone working in the following roles:
- Software Engineers
- IT Professionals
- Data Professionals
- Product Managers
- AI Professionals
- ML Engineers
- Data Scientists
- Aspiring Generative AI
- Prompt Engineers
Course overview
Master Generative AI with this state-of-the-art program offered by Simplilearn. Delve into prompt engineering, large language models, attention mechanisms, RAG, and LLM fine-tuning. Gain expertise in essential tools and pave the way for the future of intelligent systems.
Course highlights
- 50-60 hours of instructor-led online classes
- Access to hands on projects
Key learning outcomes
Python basics
- Gain proficiency in procedural and object-oriented programming using Python, recognizing its advantages.
- Install Python and its integrated development environment; familiarize with Jupyter Notebook for practical applications.
- Understand Python's fundamental concepts, including identifiers, data types, operators, loops, variable scope, indentations, comments, and string functions.
Essentials of Generative AI, Prompt Engineering & ChatGPT
- Understand the fundamentals, mechanisms, and significance of ChatGPT and generative AI, including explainable AI.
- Apply prompt engineering techniques and explore diverse applications, use cases, and fine-tuning methods for ChatGPT.
- Examine the potential of generative AI to revolutionize industries and gain in-depth knowledge of prominent generative AI tools.
Applied Generative AI
- Gain comprehensive skills in generative models, including LLMs, VAEs, and GANs, and understand their architectures and capabilities.
- Learn advanced prompt engineering techniques, fine-tuning, and customizing LLMs for specific applications.
- Understand the critical role of benchmarking in evaluating and comparing the performance of generative AI models.
Generative AI Governance
- Understand the importance of governance in generative AI, including ethical considerations, regulatory challenges, accountability, and risk mitigation.
- Learn the ethical foundations of AI, responsible development, bias mitigation, privacy, and setting up AI governance committees.
- Gain knowledge in identifying and mitigating AI project risks, integrating governance in AI projects, and understanding regulatory trends and career opportunities in AI governance.
Why Choose ILX learning?
graduates
corporate clients
customer satisfaction
Companies we work with
ILX provides bespoke and personalised training solutions that drive measurable business impact and deliver value for teams of all sizes.