Duration: 5 days – 35 hrs
Generative AI for Developers Course Overview
This Generative AI for Developers course is designed to equip developers with the skills and knowledge required to leverage generative AI technologies in their applications. It covers the fundamentals of generative AI, key algorithms and models, practical implementation techniques, and ethical considerations. By the end of this course, participants will be able to create, implement, and optimize generative AI models for various use cases.
Objectives
- Understand the fundamentals of generative AI and its applications.
- Learn about key generative AI models, including GANs, VAEs, and transformer-based models.
- Gain hands-on experience with popular generative AI frameworks and tools.
- Develop and deploy generative AI models for real-world applications.
- Address ethical considerations and challenges in generative AI.
Audience
This course is ideal for professionals seeking to master Generative AI for Developers, including:
- Software Developers and Engineers – Professionals looking to integrate generative AI into their applications and enhance their AI skills.
- Data Scientists and Machine Learning Practitioners – Those expanding their expertise to include generative models for data augmentation and predictive modeling.
- AI Enthusiasts and Researchers – Individuals exploring generative AI concepts and their practical applications.
- Graduate Students in AI and Related Fields – Students seeking hands-on experience in generative AI.
- Product Managers and Technical Leads – Professionals guiding AI-driven product development and implementation.
- AI Startup Founders and Innovators – Entrepreneurs leveraging generative AI for innovative applications and solutions.
Prerequisites
To succeed in the Generative AI for Developers course, participants should have:
- Proficiency in Python.
- Understanding of basic machine learning concepts and algorithms.
- Basic knowledge of neural networks and deep learning frameworks (e.g., TensorFlow, PyTorch) is helpful but not mandatory.
Course Content
Day 1 – Python
- Python Concepts
- Python Operators
- Python Data Types
- Python List
- Python Tuples
- Python Dictionary
- Python File Handling
- Python Functions
- Python Variables
Day 2 – Machine Learning
- ML Foundation
- Resource Guide
- ML Concepts
- Numpy
- Pandas
- Numpy and Pandas
- Supervised Learning
- Unsupervised Learning
- Linear Regression
Day 3 – Generative AI Foundation
- GenAI Course Overview
- Define GenAI
- GenAI Demo
- Lab: Generate Videos in a Single Prompt
- Applications of GenAI
- Technologies Behind GenAI
- Ethics and Legal Considerations in AI
- Lab: Generate PPT in 30 Seconds
- Managing GenAI Projects
- Security in GenAI
- Future of AI
- Lab: Generate AI Voice in a Single Prompt
Module 2: Prompt Engineering
- Define Prompt Engineering
- Prompting Techniques
- Behind the Scenes: Prompt to Output
- Lab: Prompt with ChatGPT 3.5
- Lab: Prompt with ChatGPT 4.0
- Lab: Prompt with Anthropic Claude
- Lab: Prompt with Google Gemini
Module 3: Natural Language Processing
- Introduction to NLP
- Applications of NLP
- Evolution of NLP
- Challenges in NLP
- NLP Tasks
- NLP Pipeline
- NLP Tools and Libraries
- Lab: Email Spam Filtering
- Lab: Text Summarization
- Lab: NLP Data Preprocessing
Day 4 – Dive into LLM
- Introduction to LLM
- Applications of LLM
- Advantages of LLM
- Custom vs. Fine-Tuned LLM
- Multimodal LLM
- Lab: Access OpenAI Programmatically
- Lab: OpenAI LLM – NLP Tasks
Module 5: Developing Generative AI Applications
- Lab: Develop PDF Chatbot
- Lab: Develop Text & AI Voice-Integrated GenAI Apps
- Lab: Develop a Chatbot for Website PHI Data
Day 5 – Langchain
- Introduction to Langchain
- Overview of Langchain Architecture
- Use Cases of Langchain
- Integrating Langchain with Existing Systems
- Lab: Setting Up Langchain Environment
Module 8: Developing Applications with Langchain
- Lab: Build a Simple Chatbot Using Langchain
- Lab: Langchain with Google Search Integration
Module 9: Public Cloud GenAI Solution Demo
- Introduction to AWS Bedrock – Demo
- Introduction to Google Vertex AI – Demo
- Introduction to Azure AI Studio – Demo
Conclusion
The Generative AI for Developers course equips participants with essential skills to leverage AI in real-world applications. Covering Python fundamentals, machine learning, large language models, and LangChain, this course ensures hands-on experience through practical labs. By the end of Generative AI for Developers, attendees will confidently build and deploy AI-driven solutions, from chatbots to generative models. With a strong focus on ethical considerations, security, and future trends, this course prepares developers to innovate with AI responsibly. Whether you’re an engineer, researcher, or entrepreneur, this training empowers you to harness generative AI for cutting-edge applications.
