GenAI Training Program
Course Overview
The GenAI program is designed to introduce GenAI to software developers. This course focuses on practical applications of AI-driven tools, enabling developers to enhance productivity, automate code generation, and build AI-powered applications.
This curriculum will cover foundational concepts, industry-leading AI models, and real-world implementations, integrating AI solutions into workflows. The ecosystem of GenAI tools and concepts needed for GenAI based development like RAG, CAG, VectorDB, LangChain etc would be covered.
The course will cover ethical AI usage, security considerations, and best practices for responsible AI development. While the course will cover the concepts of fine tuning, creation of LLMs from scratch is outside the scope.
FAQ about generative AI
Introduction to Generative AI
Overview of AI and Machine Learning Evolution of Generative AI, Attention Key Concepts: NLP, Deep Learning, Transformers Applications of Generative AI in Software Development
Foundations of Generative Models
Neural Networks & Deep Learning Basics Introduction to Autoencoders and GANs Transformers & Attention Mechanism Large Language Models (LLMs): GPT, BERT, T5, Claude, Mistral
Hands-on with Generative AI Tools
OpenAI GPT (ChatGPT) Google Gemini AI Hugging Face Transformers LLM models on Cloud(AWS + Anthropic) LangChain and Prompt Engineering
Generative AI for Code Generation
AI-Powered Code Assistants (GitHub Copilot, Tabnine, Llama coder) AI for Code Refactoring & Debugging Automating Documentation with AI Best Practices & Limitations
Building AI-Powered Applications
Integrating Generative AI in Software Development Introduction to LangChain, RAG, CAG, chaining and output parsers Handling Long Contexts with Memory External data sources and using Vector Databases for Contextual Awareness Implementing RAG with LangChain and Vector Stores (FAISS, Pinecone, ChromaDB) Using APIs for AI-Generated Content Developing AI Chatbots & Virtual Assistants Case Studies: AI-Powered Apps
Integrating External sources and Agentic AI
Connecting LangChain to External APIs (Google Search, etc.) Introduction to concept of Agent
Ethical Considerations & Challenges
Bias & Fairness in Generative AI Data Privacy & Security Concerns AI Regulation & Compliance Responsible AI Development
Advanced Topics & Future Trends
Fine-tuning LLMs for Custom Applications Multi-modal AI (Text, Image, Audio) AI in DevOps & Automation Future of Generative AI in Software Engineering
Why Trust Us? Our Expertise & Accreditations
Our GenAI Training Program is designed by industry experts with hands-on experience in AI-driven development. We are partnered with leading tech organizations and hold accreditations in AI ethics and security, ensuring you receive cutting-edge, responsible AI training.
Program Overview
Master Generative AI for Development
The GenAI Training Program equips developers with practical skills to integrate AI into software workflows. Learn to automate coding, build AI-powered apps, and leverage tools like LangChain, RAG, VectorDBs, and LLMs (GPT, Gemini, Claude, Mistral). This course balances theory with hands-on labs, covering ethical AI usage, security, and real-world implementations.
What Sets Our Program Apart?
- Learn from AI practitioners, not just theorists.
- Ethics-first approach: Bias mitigation, privacy, and compliance.
- Hands-on labs with OpenAI, LangChain, and VectorDBs.
- Future-proof curriculum: Covers multi-modal AI, Agentic AI, and DevOps automation.
Ideal Participants: Who Should Enroll?
Software Developers
Automating code generation (GitHub Copilot, Llama coder).
AI Engineers
Building RAG apps, chatbots, and virtual assistants.
Tech Leads
Integrating AI into DevOps and workflows.
Data Scientists
Expanding into generative AI applications.
Prerequisites: Basic Python and software development experience.
Learn by Doing: Real-World Projects
Lab 1: Hands-on with Generative AI Tools
- Create OpenAI setup
- Create LangChain setup
Lab 2: Generative AI for Code Generation
- Configure Llama on IDE and show code generation, refactoring and documentation
Lab 3: Building AI-Powered Applications
- Simple demo for concepts of chaining, output parsers
- Create an app to use RAG and VectorDB
Lab 4: Automate workflows
- Create an app to automate a workflow
Flexible Learning
Duration
6–8 weeks (self-paced or instructor-led).
Mode
Live Online / On-Site / Hybrid.
Corporate Training
Customizable for teams.
Success Stories: Industry Transformations
Case Study 1: AI-Powered Code Refactoring
A fintech company reduced code review time by 40% using AI-assisted refactoring tools covered in this program.
Case Study 2: RAG for Customer Support
An e-commerce firm deployed a LangChain + VectorDB chatbot, cutting response times by 60%.
Skills You’ll Master: Program Outcomes
Automate coding
With AI assistants (GitHub Copilot, Llama).
Build RAG apps
Using LangChain and VectorDBs.
Engineer prompts
For GPT, Gemini, and Claude.
Develop ethical AI
Solutions with bias and privacy safeguards.
Deploy AI workflows
In DevOps and cloud environments.
Ready to Transform Your Career? Enroll Now!
FAQ About Addressing Enterprise Generative AI Developer Training Program
How does the Generative AI Developer Training Program help enterprises implement AI solutions at scale?
The Generative AI Developer Training Program helps enterprises implement AI solutions at scale by offering access to pre-trained models, scalable infrastructure, and tools for fine-tuning with proprietary data. It includes APIs, SDKs, and integration templates that accelerate deployment, along with governance features to ensure responsible AI use. With hands-on labs and expert resources, it upskills teams while enabling rapid prototyping and enterprise-grade implementation. By leveraging pre-trained models and no-code/low-code tools, the program can help organizations skip the need for extensive in-house AI training, streamlining adoption and reducing costs. Majority of the enterprise problems do not req uire a custom AI training and can be solved by leveraging the GenAI models aided by suitable prompts and fine tuning thus eliminating the need to reinvent the wheel, reducing lead time and costs.
What makes this Generative AI Developer Training Program different from other Generative AI Courses?
What sets this Generative AI Developer Training apart is the focus of this course. The trainers of this course come from the industry background with decades of experience in implementing enterprise scale applications and systems. Having rich experience of real-world problems and awareness of limitations of earlier approaches, this course has enterprise-focused, hands-on approach—combining practical implementation with scalable deployment tools tailored for real-world business needs. Unlike generic AI courses, it goes beyond theory to offer access to pre-trained models, fine-tuning capabilities, integration frameworks, and cloud infrastructure optimized for production. It also emphasizes responsible AI, security, and governance, which are crucial for enterprise adoption. Additionally, its modular structure, industry use cases, and role-based learning paths ensure relevance for developers and AI/ML engineers —bridging the gap between experimentation and enterprise impact.
Is the Generative AI Developer Training Program suitable for enterprise AI/ML engineers and software developers?
Yes, enterprise AI/ML engineers and software developers are the primary audiences for this course. It is designed to deepen technical expertise in model fine-tuning, prompt engineering, and deployment at scale. The course covers advanced use cases, integration with enterprise systems, and performance optimization, equipping professionals to build secure, efficient, and production-ready GenAI solutions. With hands-on labs, real-world scenarios, and access to enterprise-grade tools, it aligns with the practical needs of engineers and developers working in complex business environments.
What real-world use cases does the Generative AI Developer Training Program cover for businesses?
Learning a tool is only a small part of getting equipped to use it in enterprise use cases. When this Course covers real-world business use cases across key functions such as customer service, content generation, or personalized recommendations it focuses not only on how to call the underlying LLM APIs and consume the content but also the ecosystem of tools and platforms and the decision making process of making the best of the ecosystem. It also explores applications in knowledge management, internal search, and workflow automation, helping businesses streamline operations, improve efficiency, and enhance user experiences using generative AI tools.
How does the Generative AI Developer Training Program help enterprises integrate AI into their existing workflows?
The Generative AI Developer Training Program helps enterprises integrate AI into existing workflows by offering hands-on training, real-world projects, and guided implementation frameworks tailored to business needs. It teaches teams how to embed generative AI into current tools and systems using APIs, automation pipelines, and low-code platforms, ensuring seamless adoption. The bootcamp also covers model integration, and deployment best practices, enabling enterprises to operationalize AI quickly while maintaining security, compliance, and scalability across workflows.
What are the prerequisites for enrolling in the Generative AI Developer Training Program?
The prerequisites for enrolling in the Generative AI Developer Training Program typically include a basic understanding of Python programming, familiarity with machine learning concepts, and experience working with APIs and cloud platforms (for deployment). Since it is a hands-on course, and trainers are there to support, there should be no reluctance or fear of trying out the concepts in practice.
How does this Generative AI Developer Training Program support AI governance, security, and compliance?
Generative AI governance, security and compliance is an evolving area. But even where best practices are not settled, industry best practices still hold good. This Generative AI Developer Training Program supports AI governance, security, and compliance by integrating best practices into its curriculum, including ethical AI design, bias detection, model explainability, and data privacy protocols. It trains participants on how to implement audit trails, access controls, and monitoring tools to ensure responsible AI usage. The course also covers compliance with industry standards and regulations such as GDPR and HIPAA, equipping learners to build and deploy AI solutions that are not only effective but also secure, transparent, and aligned with enterprise and legal requirements.
Can the Generative AI Developer Training Program be customized for our industry-specific AI needs?
Yes, the Generative AI Developer Training Program can be customized for industry-specific AI needs. It is designed with flexible modules, tailored use cases, and role-based learning paths that align with the unique challenges and goals of different sectors—such as finance, healthcare, retail, manufacturing, and education. So while the basic know-how and the basic exercises are common, the use cases and exercises can be tailored for familiarity with a particular industry. Enterprises can choose relevant tools, datasets, and implementation scenarios to ensure the training is directly applicable to their domain, enabling faster adoption and more impactful outcomes.
What AI models and frameworks are covered in the Generative AI Developer Training Program, and how do they benefit enterprises?
The Generative AI Developer Training Program covers a range of advanced AI models and frameworks, including foundation models like GPT, BERT, Llama etc., along with frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, and LangChain. However, the extent of hands-on would be limited by duration, need, and interest of the participants. These tools enable enterprises to build applications for natural language processing, text generation, summarization, code completion, image creation, and more. By learning to work with these models and frameworks, enterprises can develop custom, scalable, and efficient AI solutions, reduce development time, and gain a competitive edge through automation, personalization, and enhanced decision-making.
How can CTOs and tech leaders measure the ROI of investing in an Enterprise Generative AI Course?
CTOs and tech leaders can measure the ROI of investing in an Enterprise Generative AI Course by tracking key metrics such as reduced development time, faster AI adoption, and improved productivity of technical teams. ROI can also be gauged through cost savings from automation, increase in AI-enabled solutions delivered, and business impact of implemented use cases (e.g., enhanced customer experience, operational efficiency). Additionally, upskilled teams contribute to reduced dependency on external vendors, better innovation throughput, and improved compliance and governance, all of which drive long-term value and strategic advantage.
How does the Generative AI Developer Training Program ensure hands-on, project-based learning?
The Generative AI Developer Training Program ensures hands-on, project-based learning by incorporating real-world labs, guided coding exercises, and end-to-end mini-projects throughout the curriculum. Participants work with actual datasets and pre-trained models, building applications like chatbots, content generators, and summarization tools. The course also includes capstone projects, where learners design, develop, and deploy generative AI solutions, end to end, tailored to business use cases—reinforcing skills through practical application. This approach helps bridge the gap between theory and real-world implementation, ensuring learners are job- and project-ready.
What are the different delivery modes available for the Generative AI Developer Training Program?
The Generative AI Developer Training Program is offered in as live virtual instructor-led sessions, in-person workshops, and customized as per enterprise. This allows individuals and organizations to choose formats that align with learning preferences, and domains – ensuring the participants get the examples that are near to their own work domain.
How soon can teams start deploying AI applications after completing the Generative AI Developer Training Program?
Right away. Teams can start deploying AI applications immediately after completing the Generative AI Developer Training Program, as the course is designed with a practical, deployment-ready focus. By the end of the training, participants gain hands-on experience with real-world tools, pre-trained models, and integration workflows, enabling them to prototype, test, and scale AI solutions quickly within their enterprise environments.
How does the Generative AI Developer Training Program help enterprise teams stay ahead in AI adoption?
It is safe to say that Generative AI is the future in near to mid term. The Generative AI Developer Training Program helps enterprise teams stay ahead in AI adoption by equipping them with cutting-edge skills, practical tools, and industry-aligned best practices for building and scaling generative AI solutions. It ensures teams are trained on the latest models, frameworks, and deployment strategies, while also emphasizing responsible AI, governance, and integration with business systems. By fostering innovation and reducing reliance on external expertise, the program enables enterprises to accelerate AI adoption, drive competitive advantage, and future-proof their workforce in a rapidly evolving tech landscape.