3.0 Agentic AI Specialisation with AgentOps Bootcamp

追加: 2026-06-04

[00:00:00]Hello all, my name is Krishna and welcome to my YouTube channel. So guys, I am super excited to announce our new boot camp or cohat and the boot camp name is 3.0 agentic AI specialization with agent ops. Now guys, uh this kind of specialization batch we just launched once in a year. Last year also we had actually launched it you know and we had an amazing response uh because we taught really really so many different topics and in this particular batch we have added more topics with respect to the recent context recent development that has been happening around us and we have also included that part in the syllabus okay so please make sure that you watch this video till the end because I'm going to talk about what all things we are going to learn in this right it would be quite amazing and trust me if recently if you're trying to learn how to basically build AI agents, agentic AI application even in your company. This way we'll be talking completely from end to end, right? Because here we have also included something called as agent ops that is nothing but agent operations.

[00:01:03]How do we go ahead and deploy? How do we make sure that we apply all the securities when we are deploying all these kind of agents? Each and every point will be discussed and we have integrated that as a separate module.

[00:01:13]Okay. So please make sure that you watch this uh video till the end. uh there are a lot of things that we we will be teaching over here. So the first thing when the batch is basically going to start the batch will be starting from June 21st 2026 and uh the classes will be between Saturday and Sunday like it'll be on Saturday and Sunday 8:00 a.m. to 11 a.m.

[00:01:33]IST. So during in the morning times uh this is the time slot that we had available. So this is suitable for US US students also it is also suitable for Indian Indian IST standard time right uh because I think in US it'll be somewhere around night uh I think uh yeah that is like 12 hours difference so and this batch will be going for somewhere around 5 to 6 months u beforehand I really want to talk about the course fee this is 8,000 rupees inclusive of GST if you are probably opening it from US or some other countries the price will be a little different the Reason is very simple. You have some payment gateway charges included, right? But for people who are in India, it is 8,000 inclusive of GST. So GST is included which goes to the government. Our main aim is that based on the number of months, we charge every month 1,000 rupees. So this batch will be going around 5 to 6 months mostly more than 6 months it can go.

[00:02:28]Okay. So every month,000 means 6,000. So 6,000 plus GST. It comes somewhere around 8,000. Okay. I think it is 6,300 plus inclusive of GST. Okay. Now these are all the information. Okay. Now the next thing is that um what all things we are going to learn. Okay. So first of all just go ahead and click on enroll now. Okay. Once you go ahead and click on enroll now we have created very detailed syllabus. Okay. So over here all the information is basically given.

[00:02:56]Um you can go ahead and just check it out. So this is the detailed syllabus.

[00:03:01]Okay. The entire detailed syllabus. What all things we are going to cover? how we are going to cover you know uh everything that we are going to cover along with this one more very important information that I really want to talk about the mentor for this particular course will be Mayank Agarwal okay so I hope you know about Mayank Agarwal he has taken lot of live sessions in our uh YouTube live he also taken a lot of batches in Krishna Academy amazing mentor uh with lot of amazing concepts he has he also run his own consultancy where he talks to clients so he will definitely be able to give give you a lot of experience out there. Okay. Now what we are basically going to do is that over here is the entire detailed syllabus. You can just go ahead and open the PDF. Along with that there is also an interactive syllabus just to make you understand what all things we are going to specifically cover. Okay. So now I'll just go ahead and hide my face so that you can focus over here. So aentki and geni agent optops with cloud 3.0. So uh one more amazing thing is that with this specific batch we will also be giving you the access of 2.0 batch. Okay. the previous batch that has gone completed.

[00:04:05]Uh that also excess will be giving this also access will be giving and here we'll be talking about the live classes and after the live classes is done we'll also be giving you the recording videos.

[00:04:15]Okay. So 5 to 6 months, 30 modules, nine projects, three cloud platforms that we are going to basically do. If you go ahead and just click the road map, you'll be able to see on uh week 1 to three what we are going to learn and all everything is basically there. But I just want to talk about what all things we will be learning, right? So everything you are going to master first we will be learning about various agentic frameworks like lang chain lang graph openai SDK agents SDK Google ADK AWS strands cre lama index n and lang flow okay along with that we're also going to use cloud and coding agents so we will be talking about cloud code open claw name claw her agent coder cla open code anti-gravity this will probably give you almost everything that you specifically require with respect to different different coding agents also Then we are going to talk about different protocols and standards which are like MCP and A2A. Then we'll also be talking about memory and knowledge like how we'll be talking about MEMS zero.

[00:05:10]We'll be talking about langraph checkpointing, lama index memory, graph rag, different kinds of memories that can be integrated with an agentic AI applications or a AI agent. Right? So that is what is very important because building an AI agent just with an open source library is very easy. But to take it into the production and show how the deployment is basically done. What are things we really need to take care in terms of security in terms of memory that is what is specifically required in industries. Okay. Then core concepts you'll be able to see we'll be learning about rack agentic rack context engineering prompt engineering pentic vectors db agent evaluation agent security guard rails fire stav so many different different topics are there. Uh you'll be seeing that we'll be doing deployments with the help of CI/CD.

[00:05:53]Again we'll be using dockers, GitHub actions, fast API, bentoml, streamlate, gradio. So there are lot many things that we're going to learn. Along with that we'll be having different different cloud platforms like AWS, GCP, Azure VPS and we'll also be having we'll also be seeing different different LLM providers like OpenAI, Anthropic, Germany, Grock, Olama, Bedrock, Azure, OpenAI. So everything we are specifically covering if you really want to just go ahead and see with respect to the road map. So here is the phase zero phase one uh we'll be learning this. Then the phase two we'll be learning about the cloud ecosystem and coding agent. Phase three extended frameworks. Phase four production cloud projects. So step by step we'll be covering each and everything. Okay. Now one very important thing that I really want to talk about.

[00:06:35]Okay. See whenever you develop any kind of agents. Okay. Let's say that this is one of my agent. Okay. Developing agent is or an agentic AI application is very simple. Okay. Let's say that I'm using a cloud code which is like my coding agents and I'm building this. If I'm talking about this agent application, this may be some kind of workflow. It can let's say if I'm talking about this a uh this is my agent A and this agent A basically learns runs this agentic workflow. When we are running this agentic workflow, it's fine. It uses some kind of L models uh based on a specific input. It uses some other tools and do all this specific work, right?

[00:07:15]Even though you are creating a deep agent, it'll be doing all these things.

[00:07:19]But in this stage like in 2026, the most important thing is that how do we take this specific agent to production? That is the most important thing. Okay, production let's say with respect to enterprise level, how do I go ahead and make it as an enterprise application so that it will be able to serve millions of customers out there, right? So there we basically talk about scale, we talk about security because security is very important, right? Because this AI agent will be working independently. Yes. Uh human in the loop approvals can be applied but they are still lot of things recently have heard that one of the company right agent deleted the entire production database just in 9 seconds.

[00:08:01]So you obviously want that your AI agent should not perform like this right and there are multiple steps how we can basically identify how we can make our agents work right one of the step basically is like you need to know how to apply a guardrail okay so let's say there is something called a concept of guardrails you should know how to basically go ahead and apply a guardrail let's say uh you have developed an AI agents how do you go ahead and check it with respect to the evaluation so for that you have various evaluation frameworks you have uh evaluation metrics right that you can basically apply on this particular AI agents and you can see that how well it is basically performing right along with this there's a concept of something called as LM gateways okay L&M gateways basically says that okay fine if one open AI API is not working then how you can basically go ahead and use some other APIs right it's it has lot of routing functions with respect to LM gateways and I made a very detailed video in my YouTube channel also so how to implement LLM gateways by using different different frameworks that is available right like light LLM port key each and everything right and within this LLM gateways there are concepts like caching you can actually go ahead and apply caching over there you can apply other concepts over there you can apply even guardrails and evaluation frame uh metrics over here also just to see that how well the agent is basically performing and then based on the working of the agents you can also basically observe what all outputs it's basically creating so for that you need to use some observability tools and there are multiple observ ility tools that are actually available. Let's say one of the example is like lang right. With the help of lang symmetry, you'll be able to understand let's say if you have used langraph and developed this entire agentic workflow, you'll be able to track each and everything with respect to that particular workflow. Right? After doing all these things, how do you go ahead and take this into the production? How do you go ahead and deploy it in cloud platforms like GCP, AWS, how do you go ahead and use different different LLM models? Everything is basically getting covered, right? That's the most important thing, right? And that is what is about 3.0. But still the major question comes kish what are the prerequisites whom this particular batch is basically applicable to right. So guys for this particular batch you really need to know good Python programming language a basic knowledge of machine learning deep learning and generative AI will be more than sufficient to get you get started and be ready with what kind of applications we are currently developing in the industries. I have spoken to a lot of product managers, lot of developers, lot of architects, you know, just to understand like what kind of skill sets are currently being required and this is one of the kind of skill set that is actually required in every companies that you are probably going because here we are not only learning how to develop AI agents or how to probably develop an agentic application. Here we also learning like how we can actually use coding agents along with our coding journey along with that how do we probably take it apply it all the necessary things so that it is taken into production right so guys before I end this specific video uh definitely go ahead and try out this specific boot camp along with this I have a very special surprise for you so uh it on 7th June 2026 it's going to be 2 years of running Krishna Snack Academy. Okay. And I know many of you have learned from us.

[00:11:26]Uh I hope you have got an amazing experience. I hope many of you are able to make successful career transition because our focus is to teach the most trending things and probably serve everyone who want to actually learn AI AI uh in a point that you actually do something amazing in the companies itself, right? And obviously our courses are affordable, right? So on this specific occasion I would like to probably say that we will be providing 15% off in all our courses. Use the coupon krish 15. So this particular course is somewhere around 8,000 rupees INR. Uh after applying discount you will be able to after applying this particular coupon code you'll be able to get 1100 to 1200 discount and then I think your course fees will be somewhere around 6,800 inclusive of GST. Again as said we are always going to be affordable. We always going to be bootstrapped and we'll teach we'll try to teach in a way that definitely matters in the industry and these all things are basically happening because we are doing a lot of research and discussions even with people who are in companies who are in architect position who are in lead position just to understand what is basically happening in the IT companies and based on that we come up with these all amazing courses. So yes this was it from my side. I'll see you in the next video.

[00:12:41]Have a great day. Thank you and all.

[00:12:43]Take care. Bye-bye.