Explore Generative AI, LangChain, Prompt Engineering. Build, Deploy, Optimize Gen AI Models Apps with Python.
β±οΈ Length: 20.1 total hours
β 4.54/5 rating
π₯ 12,634 students
π August 2025 update
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- Course Overview
- Master Generative AI: This bootcamp offers a comprehensive journey from core AI principles to deploying advanced Generative AI solutions, covering modern architectures and practical applications.
- Complete Development Cycle: Learn the entire Generative AI pipeline: advanced data preparation, model training (Transformers), intelligent prompt engineering, robust deployment, and continuous optimization.
- Build Real-World Applications: Gain hands-on experience by building, refining, and deploying diverse Generative AI applications, creating a strong portfolio of practical, innovative projects.
- Harnessing Modern AI Architectures: Delve deep into the power of Large Language Models (LLMs) and Transformer architectures, understanding their core mechanisms to build intelligent systems capable of generating human-like text, code, and more.
- Requirements / Prerequisites
- Proficient in Python Basics: A solid understanding of Python programming fundamentals, including syntax, data structures, and functions, is essential for engaging with the courseβs practical coding exercises.
- Curiosity for AI: While no advanced mathematical background is strictly required, a keen interest in artificial intelligence and a problem-solving mindset will maximize your learning experience.
- Skills Covered / Tools Used
- Deep Dive into Transformers: Understand the intricate workings of Transformer architectures, including self-attention mechanisms and positional encoding, crucial for cutting-edge Natural Language Processing and Generative AI.
- Advanced Prompt Engineering: Master sophisticated prompt crafting, exploring methods like few-shot learning, chain-of-thought, and iterative refinement to optimize LLM outputs for various scenarios and achieve desired outcomes.
- LangChain for AI Orchestration: Become proficient in using LangChain to build multi-agent systems, integrate diverse data sources, and simplify complex Generative AI application development and deployment workflows.
- Production Deployment (MLOps): Learn industry best practices for deploying Generative AI models, including containerization (e.g., Docker), cloud integration, API creation, and MLOps strategies for scalability and maintenance.
- Ethical AI and Bias Mitigation: Address critical ethical considerations in Generative AI, identify potential biases in models and training data, and learn strategies for developing responsible, fair, and transparent AI systems.
- Optimizing Vector Databases: Explore advanced techniques for integrating and tuning vector databases for efficient similarity search, data indexing, and scaling large-scale embedding retrieval in AI projects.
- Custom LLM Fine-tuning: Discover methods for fine-tuning pre-trained Large Language Models on specific datasets to adapt them to unique domain knowledge or generate highly specialized content for custom applications.
- Benefits / Outcomes
- Become an Expert Gen AI Developer: Acquire comprehensive skills to confidently design, implement, and manage advanced Generative AI solutions, preparing you for impactful roles across various industries.
- Develop a Strong Portfolio: Build a compelling collection of practical Generative AI projects, showcasing your technical abilities and problem-solving skills to prospective employers and enhancing your career prospects.
- Future-Proof Your AI Career: Gain adaptable knowledge and methodologies that will enable you to continuously learn and innovate with new Generative AI models and frameworks, staying ahead in the rapidly evolving field.
- Unlock Creative AI Applications: Harness AI to create novel applications, automate complex tasks, and generate unique content, expanding possibilities across diverse industries and fostering innovation.
- PROS
- Comprehensive & Modern Curriculum: Offers a well-structured learning path, updated for August 2025, covering the latest advancements in Generative AI, Natural Language Processing, and Transformer technologies.
- High Student Satisfaction: A strong 4.54/5 rating from over 12,000 students confirms high-quality instruction, relevant content, and an effective, positive learning experience.
- Hands-on Practical Focus: Emphasizes project-based learning, enabling participants to build, debug, and optimize Generative AI models and applications with real-world relevance.
- Market-Ready Skills: Develop highly sought-after skills in LangChain, prompt engineering, and production Generative AI deployment, significantly boosting employability in the AI industry.
- Engaging & Clear Instruction: Course design facilitates deep understanding through clear explanations, practical examples, and challenging exercises, ensuring an engaging and effective educational journey.
- CONS
- The intensive nature and broad scope of the 20-hour curriculum might require extra self-study or prior familiarity for absolute beginners to fully grasp every advanced concept.
Learning Tracks: English,Development,Software Engineering
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