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
Programs to help developers get a high-paying job by learning the internals of how things work and mastering system design.
Recorded Classes
Self-paced recorded classes for AI and ML, and Android. Simple explanations for complex topics.
Two Programs
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
100 hours of recorded classes to master AI and ML at your own pace by learning the internals of how things work and system design to get a high-paying job in AI.
View NowAndroid Development
70 hours of recorded classes to master Android Development at your own pace by learning the internals of how things work and system design to get a high-paying job in Android.
View NowYour Teacher
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.
What is an AI Agent Engineer?
An AI Agent Engineer is an AI Engineer who specializes in building AI agents, which are systems built around an LLM that decide what to do next, use tools, and keep working step by step until a goal is reached.
How does flow matching train a generative model?
Flow matching trains a generative model by teaching it the direction and speed to move from a random noise point toward a real data point, like a photo. During training, it draws a straight line between a noise point and a real data point and asks the model to predict the movement along that line.
What is Policy Gradient? The REINFORCE Algorithm Explained
Policy Gradient is a way to train an AI agent by directly making the actions that led to good results more likely, and the actions that led to bad results less likely. REINFORCE is the simplest algorithm that does this.
How does a voice agent truncate its memory to only what the user actually heard?
A voice agent truncates its memory by finding out how much of its reply was actually played through the speaker before the user interrupted, and then cutting its saved reply down to only those words, so that its memory matches what the user really heard.
What is a Value Function? Q-Learning Explained Step by Step
A Value Function gives a number that tells an agent how much total reward it can expect from a situation, and Q-Learning is a method that learns these numbers for every situation and action by trial and error.
Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are neural networks built to understand images. They slide small pattern detectors over a picture to find edges, shapes, and objects, step by step.