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Best Generative AI Course for Cloud & Solutions Architects

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By Vikram Singh

Updated on Oct 9, 2026

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  • Cloud and Solutions Architects are currently well positioned for future success. They know how to design solutions for scaling, security and reliability and possess the systems thinking foundations which most technology experts try to develop throughout many years of their career. However, the workload that is arriving on their roadmap is something that cannot be ignored anymore. 

  • Generative AI is changing the requirements of enterprises regarding the people designing their architecture. Understanding how to build an architecture for predictable and consistent behaviour is a highly valuable skill that will only get you far if complemented with another one – designing an architecture for LLM-based systems, supporting autonomous AI agents, building a secure RAG pipeline, and implementing generative AI in production-ready state. 

  • The problem is that most architects developed their skills before the emergence of generative AI. Infrastructure skills are well-developed, however, the unique design patterns of these new workloads are unknown to many experts yet. 

  • This is exactly the reason for choosing the correct generative AI program by the Cloud and Solutions Architects who want to lead the direction of enterprise architecture development. 

Why This Program Is Ideal for Cloud & Solutions Architects 

This course material aligns directly with the capabilities of an architect, as most of what they do relate to system design, scalability, and dependability as opposed to greenfield development. 

  • Designing infrastructure will apply directly to the compute-latency-cost considerations of LLM workloads 

  • Integration of APIs and systems is a given at the start, and not something taught from the basics 

  • Designing distributed systems will be directly applicable to architecting the multi-agent workflows involved 

  • Security and access control experience will directly apply to the governance considerations of generative AI 

  • Scale design experience will underpin the architecting of RAG pipeline and vector retrieval layer 

What You'll Learn Throughout the Program 

The curriculum adheres to a linear progression starting with basics and then going on to cover systems in production rather than systems that are just functioning in demonstration mode. 

  • GenAI and LLMs foundations – transformers and foundation models   

  • Advanced prompting and RAG – hybrid search and reranking  

  • LLM fine-tuning and alignment using PEFT, LoRA, and QLoRA  

  • Multimodal and Agentic AI – agents workflows with planning and tools  

  • Deployment and optimization – latency, costs, and AI safety 

Practical Learning Through Real Projects 

This course will be centered on five deliverables rather than isolated assignments; therefore, each module results in something that works.  

  • Enterprise RAG system with evaluation pipeline for the retrieval accuracy 

  • Open-source LLM with fine-tuning using LoRA/QLoRA and deploying it as an API 

  • Multi-agent system for multiple-step tasks execution 

  • Containerized & monitored Generative AI API for real traffic handling 

  • 2-week capstone industry project with faculty supervision 

Fees, Eligibility & Program Information 

Here's what you're signing up for, cost and eligibility included: 

  • Fee: ₹1,99,000 including taxes 

  • Seat block: ₹10,000 

  • EMI: starting from ₹6,825 per month 

  • Qualifications for application: bachelor's degree with minimum 50% marks 

  • Ideal academic background: B.Tech, MTech, B.E., M.E., B.Sc., M.Sc. in Computer Science/Information Technology/AI/Electrical & Communication Engineering/Mathematics/Statistics or MCA/BCA 

  • Others: eligible if you have at least 2 years of experience in the technology domain 

  • Skills needed: writing functions in Python, basic data structures, working with APIs, reading technical documentation, and familiarity with the basic mathematics and statistics behind common ML concepts 

  • Certificate awarded: on campus at the time of graduation at IIT Kharagpur, handed over by the Programme Director and Institute leadership 

Admission Process 

Joining the program is straightforward and only requires three steps. 

  • Fill in your details and complete your application. 

  • Get shortlisted and receive your offer letter. 

  • Block your seat.  

Why Study Generative AI at IIT Kharagpur 

IIT Kharagpur brings a few things to this program that are hard to find combined in a single online course. 

  • India's first IIT, founded in 1951, with 75 years of educational experience 

  • Ranked 5th in Engineering in NIRF 2025, among the top-ranked universities in India 

  • Professors who regularly publish papers in conferences like NeurIPS, ICML, ICCV, ACL, and IEEE Transactions, so the syllabus is based on research and not tutorials 

  • Classes conducted only by professors from the CSE department, with no third-party instructors involved at any point 

  • Certificate awarded after an on-campus ceremony, not just a digital one 

Conclusion 

The Cloud and Solutions Architects are already ahead of most tech professionals in terms of building robust systems. By adding your skills in Generative AI and Agentic AI on top of this, you will not only keep up but place yourself in an even more coveted position as there are already organizations fighting to recruit people like you.   

By pursuing IIT Kharagpur’s agentic AI course, which also covers Generative AI, you can build the practical skills to extend your cloud architecture experience to intelligent systems. If you are interested in enterprise architecture and its future developments, consider exploring this program.

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Vikram Singh

Vikram Singh

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Domain:

Data Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, Python, SQL, Tableau, Power BI, Content Development, Content Management, Digital Marketing

Current role in the industry :

Manager, Content Marketing

Education Qualification :

M.Sc., (Applied Mathematics)

About

Vikram Singh is a seasoned content strategist with over 5 years of experience in simplifying complex technical subjects. Holding a postgraduate degree in Applied Mathematics, he specializes in creating engaging content across domains like Applied Data Science, Machine Learning, Generative AI and Agentic AI. Vikram is proficient in industry standard tools such as Python, SQL, Tableau and Power BI, which he uses to bridge the gap between technical depth and reader clarity. His writing explores practical AI applications, data-driven decision making and the role of AI in business and financial technology. His mission is to make advanced topics more accessible to learners and working professionals, helping them understand emerging technologies and identify relevant skills for career growth.

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