Get a High-Paying Tech Job
Software engineers like you join Outcome School to achieve the outcome that is a high-paying tech job.
Designed for Outcome
A program to help developers get a high-paying job through live classes where they learn the internals of how things work and master system design.
Live classes
Live classes for 9 months. Simple explanations for complex topics.
9 months program
You can choose from "AI and Machine Learning" or "Android".
Learn from Anywhere
As this program is completely online, you can join it from anywhere in the world.
We teach Internals
To get a high-paying tech job, you must know the internals and be great at system design. Knowledge comes to those who crave for it.
Eligibility
Working professionals - anyone already working in tech but looking for a high-paying tech job by learning the internals and System Design.
Programs
You can choose anyone from the below.
AI and Machine Learning
9 months long online learning program to master AI and ML by learning the internals of how things work and mastering system design to get a high-paying job in AI.
View NowAndroid Development
9 months long online learning program to master Android Development by learning the internals of how things work and mastering system design to get a high-paying job in Android.
View NowYour Teacher and Mentor
Amit Shekhar
Founder @ Outcome School • IIT 2010-14 • I have taught and mentored many developers, and their efforts landed them high-paying tech jobs, helped many tech companies in solving their unique problems, and created many open-source libraries being used by top companies. I am passionate about sharing knowledge through open-source, blogs, and videos.
Our Students' Growth
Got Salary Hike
CTC Change: 4 LPA → 24 LPA, 9 LPA → 24 LPA, 13 LPA → 46 LPA, 20 LPA → 60 LPA
Notable Transition
Software Engineer → VP of Engineering, Software Engineer → Staff Engineer
Open Source
Worked on Open Source projects and received interview calls from Top Companies
Our students got placed in top companies thanks to their efforts.
What students are saying about us
Kiran Rao Chavan
Hi Amit, with every class that I see and hear from you, silently learning the techniques of system design skills in developing AI from scratch is phenomenal and I was impressed with "Attention is all you need" Paper explanation was next level. I have read YOLO Paper for image processing and writing python scripts after multiple attempts, but the way you give real time examples and the analogies that you give while explaining toughest things - you make it look like a cake walk. KVCache, Paged Attention, vLLM, Quantization, each and every concept that you teach is exceptional.
Aman Shekhar
Outcome School delivers deep, practical AI/ML mastery that standard degree programs simply cannot match. Under Amit’s expert supervision, the curriculum shifts you from an AI consumer to an AI builder, instead of just using tools like Claude, you build autonomous AI agents, build LLMs from scratch, playing with KVCache, code Transformer architectures line by line etc. The best part was understanding the paper "Attention is all you need", not only that now I can read and understand any whitepaper. This rigorous, code-first approach has completely transformed my career trajectory, elevating me to the official AI Focal Point in my organization and the go-to expert for all complex technical queries.
Khush Panchal
Amit has been an incredible mentor to me. Under his guidance, I navigated the world of open source, which took my journey to the next level. Amit's presence works as a catalyst in the journey of learning and growing. His insights were incredibly helpful, whether it was cracking firms like Microsoft and Blinkit, negotiating salaries, or making career decisions. His mentorship also enabled me to create major open-source libraries. I am grateful to have Amit as a lifelong mentor and look forward to creating a positive impact with him.
Recent Blogs
We publish high-quality blogs regularly for our learners.
Encoder vs Decoder in Transformers
In this blog, we will learn about Encoder vs Decoder in Transformers, the two building blocks behind almost every modern AI model that works with language. We will also see how the Encoder and the Decoder differ from each other, how each one works with simple examples, why one of them reads in both directions while the other one looks only backward, what the three types of Transformers are, and when to use which one.
What is Generative AI?
In this blog, we will learn about what Generative AI is. We will understand what the word "generate" actually means, how Generative AI is different from the older AI, how it learns from a huge amount of examples, how it creates something completely new, where we use it every day, and the limitations we must know.
Prompt Injection in LLMs
In this blog, we will learn about Prompt Injection in Large Language Models. We will also see why it happens, how an attacker uses it, why the obvious fixes fail, and how we can defend our AI applications against it in the real world.
Precision vs Recall
In this blog, we will learn about Precision vs Recall, the two numbers we use to measure how good a system is at making yes-or-no decisions. We will also see how Precision and Recall differ from each other and when to use which one, what the four possible outcomes of any such decision are, why these two numbers pull against each other, and how the cost of a mistake decides which one we must care about more.
What are Embeddings?
In this blog, we will learn about Embeddings, one of the most important ideas behind modern AI like search engines, recommendations, and chatbots. We will also see why a computer cannot compare meaning on its own, how an embedding turns meaning into numbers so that similar things sit close together, how we measure that closeness, and where we use embeddings in the real world.
What are Agent Skills?
In this blog, we will learn about Agent Skills. We will also see why we need them, what is inside a Skill, how the description makes an agent pick up the right Skill by itself, how progressive disclosure keeps the context window free, how Agent Skills differ from MCP, and how we can create our own Skill.