AI/ML for C# Developers

complete cohort information the problem every c# developer is facing right now you're a solid net developer you've shipped production code you understand solid principles, design patterns, microservices architecture but there's a problem every job description now mentions ai/ml every senior role expects you to know it every interview asks about it and when you try to learn ai/ml, you hit a wall every course is built for python developers the tutorials assume you're comfortable with jupyter notebooks, numpy arrays, and python syntax you're translating concepts in your head while trying to learn new concepts it's exhausting meanwhile, your peers who jumped into ai/ml 18 months ago are now getting architect roles at ₹35 45 lakhs you're stuck at ₹15 20 lakhs because you "don't have ai/ml experience " this cohort was built specifically to solve this problem why this cohort is different c# first, not python first here's what makes this ai/ml cohort unique most ai/ml courses python → ml concepts → maybe mention ml net at the end this cohort c# + ml net + python + azure ai = complete toolkit for net developers you learn ai/ml through the lens of technologies you'll actually use in microsoft environments ml net for building production ml models in c# azure ai services for enterprise grade deployments azure openai for integrating llms into net applications python (just enough to collaborate with data science teams) this isn't "learn python, then maybe apply it to net " this is "learn ai/ml as a net developer, from day one " who this cohort is built for you should join if you're a c# developer with 3 10 years of experience feeling the pressure to upskill into ai/ml currently earning ₹8 20 lakhs and targeting senior/architect roles at ₹25 35 lakhs+ working in net but your projects don't involve ai/ml (yet) frustrated with python first tutorials that don't translate to your work environment worried you're falling 18 months behind your peers who've already moved into ai/ml roles interviewing for senior positions where ai/ml knowledge is now expected this is not for you if you're a complete beginner to programming (you need solid c# fundamentals first) you're happy staying in your current role with no career advancement ambitions you're looking for theoretical ai research knowledge (this is practical, production focused) you can't commit to live sessions and structured learning over 6 8 weeks what you'll actually learn complete curriculum breakdown module 1 python essentials for net developers (week 1) you can't completely avoid python in the ai/ml world—data scientists use it, most ml libraries are python first, and you need to collaborate with teams using it but you don't need to become a python expert you need just enough to read and understand python ml code collaborate with data science teams use python libraries when necessary you'll learn getting your first python program running (no phd required) python data types, strings, statements, and functions object oriented programming and error handling in python modules and packages (understanding the python ecosystem) numpy and pandas (the two libraries that power 80% of data science work) the outcome you'll be able to read python ml code, understand stack overflow answers, and collaborate with data scientists without feeling lost module 2 ai/ml fundamentals the foundation (week 1 2) before you write any code, you need to understand what ai/ml actually is and when to use it you'll learn what is ai and ml? (real definitions, not buzzwords) different ways to implement ai rule based systems, machine learning, deep learning, probability models, fuzzy logic when to use ml vs when not to use ml (yes, sometimes an if statement is better) simple ml examples using both python and c# (see the same concept in both languages) the outcome you'll understand the landscape and speak the language you won't be the developer who tries to use ml for everything or avoids it entirely out of fear module 3 c# and ml net your core toolkit (week 2 3) this is where net developers get their advantage ml net is microsoft's open source ml framework designed specifically for c# developers you'll learn c# ml net introduction (why it exists, when to use it) mlcontext and mldata (the building blocks of ml net) models, features, and labels (the three concepts that define all supervised learning) understanding models through linear regression (a simple, intuitive starting point) model and mathematical formula connection (you don't need to be a math genius, but you need to understand the logic) linear vs polynomial vs exponential models (different data needs different approaches) simple examples of linear, polynomial, and exponential regression using c# and python the outcome you'll build actual ml models in c# that run in production net environments no python dependency required for deployment module 4 machine learning types and applications (week 3 4) not all ml is the same you need to know which type of ml to use for which problem you'll learn supervised vs unsupervised vs reinforcement learning (the three main categories) supervised learning deep dive regression (predicting continuous values prices, temperatures, sales) classification (predicting categories spam/not spam, fraud/not fraud) unsupervised learning deep dive clustering (grouping similar items without labels) dimensionality reduction (simplifying complex data) reinforcement learning basics q learning and deep q networks (how ai learns to play games and optimize decisions) the outcome when your manager asks "can we use ml for this?", you'll know which type of ml to recommend and why module 5 large language models (llms) and generative ai (week 4 5) this is the ai everyone's talking about chatgpt, claude, llama—these are llms and yes, you can integrate them into your net applications you'll learn llms overview gpt, claude, llama, mistral (understanding the landscape) setting context mcp (model context protocol) how to give llms the right context agent and generative ai (building ai systems that can take actions, not just generate text) orchestration using n8n (automating workflows with ai) github for ai models hugging face (finding and using pre trained models) prompt engineering personal (tone and voice) task (what you want the ai to do) context (information the ai needs) constraints (rules and limitations) format (how you want the output structured) jsonl files persona, system, rules, and settings (controlling ai behavior programmatically) the outcome you'll integrate chatgpt like capabilities into your net applications you'll build ai assistants, chatbots, content generators, and automation tools that use llms behind the scenes module 6 azure ai and openai service (week 5 6) you're a net developer your company probably runs on azure this is where everything comes together you'll learn identifying machine learning types in azure (which azure service for which ml task) automl no code machine learning (build models without writing ml code) computer vision workloads image classification (is this a cat or a dog?) object detection (where are the objects in this image?) ocr (extracting text from images) generative ai workloads on azure azure openai service integrating gpt 4, gpt 3 5 into net applications managing api keys, rate limits, and costs building production ready ai features the outcome you'll deploy ml models to azure, integrate azure ai services into net applications, and build enterprise grade ai solutions that scale module 7 live project building (throughout the cohort) theory is useless without application throughout the cohort, you'll build real projects from scratch regression project predicting house prices using ml net classification project building a spam filter in c# computer vision project image recognition using azure cognitive services llm integration project adding chatgpt like features to an asp net application end to end ai application from data collection to model training to deployment on azure the outcome you'll have portfolio projects that demonstrate your ai/ml capabilities when you interview, you won't say "i took a course " you'll say "i built this ai system—here's how it works, here's the architecture, here's how i solved \[specific problem] " your instructor shivprasad koirala this cohort is taught by shivprasad koirala , who brings 17+ years of experience training developers at fortune 500 companies his credentials asp net mvp for 6 consecutive years (microsoft most valuable professional awarded to only the top contributors globally) trained 3000+ developers across companies like accenture, bank of america, wipro, tcs, and jp morgan codeproject and dotnetfunda mvp for 8 years corporate training experience with xerox, l\&t infotech, edelweiss capital, merrill lynch, and more why this matters he understands c# developers' pain points (he was one) he knows how to explain complex ai/ml concepts in c# terms, not python terms he's trained developers in corporate environments where ml net and azure ai are the tools you'll actually use he's not an academic—he's a practitioner who's built production systems his teaching style no fluff, no theory without application deep dives into the "why" behind concepts, not just the "how" real world examples from enterprise projects direct answers to your questions in live sessions what you get complete cohort benefits 1\ live private problem solving sessions every week, you get live sessions where shivprasad walks through concepts in real time you ask questions and get immediate answers you see how to debug ml models when they don't work you learn from other students' questions (often the ones you didn't know you had) no more spending 4 hours googling "why is my ml net model returning garbage predictions" 2\ private community access join a curated network of c# developers who are exactly where you are—transitioning into ai/ml in the community get code reviews on your ml projects share resources and articles find accountability partners ask questions 24/7 (someone's always online) build professional relationships that extend beyond the cohort the reality many alumni say the community became more valuable than the course itself these are your future collaborators, referral sources, and friends 3\ lifetime access to all cohort materials ai/ml is evolving fast six months from now, you might need to revisit a concept or apply it to a new project you get permanent access to all session recordings all code samples and projects all slides, diagrams, and reference materials future updates as content gets refreshed this isn't a one time transaction it's a permanent learning resource 4\ in person mixer invite network with fellow developers, shivprasad, and other industry professionals face to face why this matters some of the best job opportunities come from conversations, not applications building real relationships beyond linkedin connections meeting people who can introduce you to opportunities 5\ career growth sessions knowing ai/ml is half the battle landing the ₹25 35 lakh role requires strategy you get dedicated sessions on resume optimization for ai/ml roles (how to showcase your new skills) linkedin positioning (attracting recruiters who are hiring for ml roles) interview preparation technical rounds (system design with ml components) behavioral questions (talking about your ml projects convincingly) salary negotiation (justifying the 40 50% jump you're asking for) 6\ networking opportunities throughout throughout the cohort connect with developers from different companies and industries build relationships with shivprasad (17 years of industry connections) get introduced to the questpond alumni network of 3000+ professionals access to future cohorts and events as an alumnus 7\ live project building from scratch you don't just learn theory—you build production grade applications architecture decisions explained as you make them debugging real problems that emerge during development code reviews and optimization techniques deployment to azure with proper devops practices your portfolio proof when you interview, you demonstrate actual working ai/ml systems you built the career transformation what this actually means for your income let's talk numbers, because this is ultimately about your career and your earning potential current state (typical for students in this cohort) 3 7 years of net development experience earning ₹8 20 lakhs per annum stuck in "developer" or "senior developer" roles interviewing for positions but losing out to candidates with ai/ml skills after this cohort you have demonstrable ai/ml skills on real projects you can speak confidently about ml net, azure ai, llms in interviews you qualify for roles previously out of reach ml engineer, ai solutions architect, senior net developer (with ml), technical lead (ai/ml) realistic salary range ₹23 35 lakhs (40 75% increase) the math cohort investment ₹20,000 40,000 (one time) expected salary increase ₹5 15 lakhs per year roi timeline 2 3 months of your first year in the new role this isn't theoretical questpond alumni have moved from service companies to product companies, from developer roles to architect roles, from ₹12 lakhs to ₹28 lakhs the reality check what you need to succeed this cohort will transform your career if you ✅ have solid c# fundamentals (you should be comfortable with oop, linq, async/await) ✅ can commit 10 15 hours per week for 6 8 weeks (live sessions + practice + projects) ✅ are willing to be uncomfortable (learning is hard; ai/ml has a learning curve) ✅ actually build the projects (watching videos ≠ learning; building = learning) ✅ engage with the community (ask questions, help others, participate) this cohort will not work if you ❌ expect to "passively absorb" ai/ml by watching videos ❌ can't commit to scheduled live sessions ❌ want to learn ai/ml but won't write any code ❌ expect instant results without putting in the work honest truth the cohort provides structure, expert guidance, community, and accountability but it doesn't do the work for you you still have to show up and code what happens after you enroll week 0 (immediately after enrollment) welcome email with cohort schedule and access instructions introduction to the community (meet your fellow students) pre cohort materials to review (optional, but recommended) setup instructions for python, ml net, azure account week 1 2 fundamentals python essentials for net developers ai/ml fundamentals and when to use what first ml net project (linear regression) week 3 4 core ml concepts supervised learning (regression and classification) unsupervised learning (clustering) multiple projects in c# and python week 5 6 llms and azure ai large language models and prompt engineering integrating openai into net applications azure ai services and deployment week 7 8 integration and production building end to end ai applications deploying to azure career preparation sessions after week 8 lifetime access to all materials continued access to community alumni network invitations future cohort access (as alumni) frequently asked questions "i'm not good at math can i still learn ai/ml?" yes you need to understand basic concepts (what is a slope, what is an average), but you don't need calculus or linear algebra for 80% of practical ml work ml net and azure ai handle the complex math you need to understand the logic, not derive equations "do i need to learn python or can i just use c#?" you'll learn enough python to understand ml code and collaborate with data science teams but the core focus is building ml solutions in c# using ml net and azure ai python is a tool in your toolkit, not the only tool "how is this different from watching youtube tutorials or taking a udemy course?" youtube tutorials are fragmented—you piece together knowledge from 20 different videos udemy courses are self paced with no accountability this cohort gives you structured curriculum designed for net developers specifically live problem solving with an expert instructor community support when you're stuck real accountability (scheduled sessions, peers expecting you) career guidance beyond just technical skills "will i be able to get an ai/ml job immediately after this cohort?" if you're currently a developer with 3 7 years of experience, this cohort positions you for senior net developer roles with ml responsibilities ml engineer roles in microsoft stack companies ai solutions architect positions you'll have the skills and portfolio projects getting the job still requires applying, interviewing, and selling yourself—but you'll be qualified where you weren't before "what if i can't attend a live session?" every session is recorded but live attendance is strongly encouraged—that's where the real learning happens (q\&a, debugging together, learning from others' questions) if you know you'll miss most live sessions, a self paced course might be better for you "is this cohort updated with the latest ai/ml trends?" yes the content is continuously updated current cohort includes latest llms (gpt 4, claude, llama) azure openai service ml net latest features modern prompt engineering techniques agent based ai systems "what's the time commitment?" live sessions 2 3 hours per week practice and projects 5 8 hours per week community engagement 1 2 hours per week total 10 15 hours per week for 6 8 weeks if you can't commit to this, wait until your schedule allows it rushing through won't give you the transformation you're paying for your next step enrollment information what you need to know cohort structure duration 6 8 weeks (intensive, time bound learning) format live online sessions + recorded materials + community batch size limited to maintain quality (typically 30 50 students per cohort) investment pricing ₹20,000 ₹40,000 (depending on early bird/regular pricing) payment options upfront or emi available roi 2 3 months of salary in your next role what's included all live sessions with shivprasad koirala lifetime access to recordings and materials private community access career growth sessions in person mixer invite project guidance and code reviews certificate of completion the bottom line you're at a decision point option 1 keep doing what you've been doing stay in your current role, earning ₹12 18 lakhs, watching peers who learned ai/ml 18 months ago move into ₹30+ lakh roles keep telling yourself "i'll learn it next year" while feeling the gap widen option 2 invest 6 8 weeks of focused learning show up to live sessions build the projects engage with the community add demonstrable ai/ml skills to your resume interview for roles that were previously out of reach negotiate a 40 60% salary increase the cohort doesn't make you a data scientist overnight but it does take you from "i should learn ai/ml someday" to "i build ml solutions in production net environments " the next cohort starts soon batch sizes are limited to maintain quality ready to transform your career? questions before you enroll? email us at questpond\@questpond com we'll answer honestly is this cohort right for your current skill level? what's the realistic timeline for career transition? how does this compare to other ai/ml programs? we'd rather tell you this cohort isn't right for you than take your money and watch you struggle but if you're a c# developer serious about adding ai/ml to your toolkit, this is the fastest, most structured path forward your move