Generative AI to AI Agent Masterclass for Software Engineers
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Unclaimed ProfileThis masterclass, led by industry expert Mohammed Fahim, offers an intensive, hands-on path for software engineers looking to transition into the rapidly growing field of Generative AI and AI Agent development. The curriculum goes far beyond basic prompt engineering to provide deep-dive technical training on building production-ready applications. Developers will master essential tools like AWS Bedrock, OpenAI APIs, LangChain (including LangChain Expression Language or LCEL), and advanced Retrieval-Augmented Generation (RAG) frameworks. By working through practical exercises in Jupyter Notebooks, students learn to calculate costs with Tiktoken, manage embeddings, query vector databases, and build fully functional AI agents. The course also bridges the gap between different model ecosystems, comparing OpenAI models (including ChatGPT 4o, Whisper, and DALL-E 3) with alternatives like Google Gemini and GitHub Copilot. For software professionals eager to future-proof their careers, this course delivers the precise architectural understanding and coding workflows needed to integrate next-generation intelligent agents into real-world software systems. With a strong focus on actual implementation rather than just theoretical concepts, this comprehensive training helps engineers transition from consuming AI to building complex, autonomous AI systems that drive business value.
About the creator
Mohammed Fahim | Generative AI
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Mohammed Fahim is a forward-thinking technology educator and systems architect specializing in the rapid evolution of Generative AI and autonomous AI agents. With a robust background in software engineering, Mohammed focuses on bridging the complex gap between theoretical artificial intelligence concepts and production-grade software development. As the creator of "Generative AI to AI Agent Masterclass for Software Engineers" on AllPros under the "raise-debar" moniker, he dedicates his career to helping developers elevate their technical standards. His teaching methodology is hands-on and project-driven, stripping away unnecessary jargon to focus on architecture, orchestrations, and deployment. Mohammed believes that the next generation of…Show more
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Learning format
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What You'll Learn
- Artificial Intelligence : Basics of AI. Key Concepts of AI, AI/ML Differences, Deep Learning. Real life examples of AI, ML, Deep Learning and Generative AI.
- Generative AI Internals : GPT (Generative Pre-trained Transformer), Gen AI timeline, Democratization of AI
- ChatGPT 4o : Effective Prompts to improve productivity. Build career - Create resume and prepare for interview. 1000+ Prompts with practical examples
- Open AI : Models, APIs, Invoking APIs using Postman, Playground, Tokens, Temperature, Pricing, Usage, Billing. Productivity versus Product development.
- Open AI Evolution: Tracing the evolution and milestones of OpenAI and ChatGPT tech stack - Examining the technological stack behind ChatGPT.
- ChatGPT alternatives : Exploring alternative models like Google Gemini and Copilot in the context of chat-based AI. Comparing DALL-E 2, DALL-E 3 & Midjourney.
- Jupyter Notebook and Jupyter Lab : Using Jupyter Lab for seamless interaction. Examples of using ChatGPT and other models within a notebook .
- Prompt Examples in Notebook : Practical examples of using prompts within Jupyter Notebooks. Tips for effective prompt formulation.
- Calculate Token Pricing - Tiktoken : Introduction to Tiktoken. Understanding token pricing and calculating costs for different interactions.
- Talk to Your Data - English Lang for SQL: Leveraging generative models for natural language interactions with data.
- Hands-on Programs for Open AI models : Whisper, DALL-E 3, and Embeddings.
- Advanced Generative AI : Embeddings, Vector DB, Fine-tuning, Zero-shot, One-shot and Few shot learning and RAG (Retrieval-augmented generation).
- Real-world Project Implementation : Hands-on project integrating OpenAI models ( ChatGPT, Whisper, Embeddings). Uses RAG and embeddings are plotted in graph.
- Generative AI Future : Will AI take away jobs - Addressing the common concern of job displacement by AI and New opportunities - Strategies for professionals
- Google Gemini : Explore the power of Google Gemini and it's various models Ultra, Pro and Nano
- Google Gemini: Image + text prompts, code generation, testing and debugging Platform with Replit integration
- Github Copilot: Revolutionizing Code Development: Discover Github Copilot's revolutionary impact on code development, enhancing productivity and efficiency.
- LangChain: Learn building LLM applications using LCEL(LangChain Expression Language) framework, RAG (Retrieval augmented generation), & building AI agents
- OpenAI Sora - Text to Video Model: Master OpenAI Sora's architecture and diffusion models.
- Will AI take away jobs or create more opportunities
Best For
- Software engineers and backend developers aiming to integrate LLMs into production-grade systems.
- Tech professionals who want to transition from simple prompt engineering to building autonomous AI agents.
- Developers looking to master technical stacks like LangChain, Vector Databases, and RAG architectures.
- Engineers interested in the cost management and API integration aspects of OpenAI and Google Gemini.
Not For
- Absolute beginners with no programming experience or knowledge of basic software development principles.
- Individuals seeking non-technical high-level marketing or business-only overviews of artificial intelligence.
- Data scientists looking for deep mathematical theory or neural network architecture research rather than application building.
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