Google Gemini AI: Python API Masterclass
DESCRIPTION
Unlock the power of advanced AI with our “Google Gemini AI: Python Mastery” course. In this comprehensive two-day program, you’ll master Google’s Gemini AI Python API through expert-led insights and hands-on learning. Starting with a Python crash course, you’ll build a solid programming foundation before diving into the architecture and capabilities of Gemini AI. Explore the power of Large Language Models (LLMs) for text generation, develop state-of-the-art chat models, and learn essential configuration techniques to optimize performance.
On the second day, delve into advanced applications with modules on integrating visual data with NLP, understanding vector embeddings, and implementing Retrieval Augmented Generation (RAG). Practical coding sessions will guide you in creating compelling AI-generated text, building personalized conversational agents, and enhancing AI responses with dynamic external knowledge sources. Designed for developers, data scientists, and AI enthusiasts, this course offers a flexible learning path to help you integrate advanced AI features into your applications and expand your expertise in machine learning.
- Beginners are welcome, as we delve into the foundational aspects of Python programming.
- MODULE 1: PYTHON CRASH COURSE
- MODULE 2: INTRODUCTION TO GEMINI AI & LLM’s
- MODULE 3: MASTERING TEXT GENERATION
- MODULE 4: DEEP DIVE INTO CHAT MODELS
- MODULE 5: CONFIGURING GEMINI AI
- MODULE 6: GEMINI VISION: MULTIMODAL INPUTS UNLEASHED
- MODULE 7: DECODING VECTOR EMBEDDINGS
- MODULE 8: RAG: RETRIEVAL AUGMENTED GENERATION
Course Fee: (per PAX)
(Physical Classroom)
Course Fee: (per PAX)
(Virtual Classroom)
RM 2,000
RM 1,400
Buying for yourself?
Write to us in the form below, we will contact you to discuss how best to fit your schedule.
Buying for a Team?
Write to us in the form below, we would be happy to talk to you about a group DISCOUNT.
Course Features
- Lectures 0
- Quizzes 0
- Duration 2 days
- Skill level Beginners
- Language English
- Students 0
- Assessments Self