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 Entropy in Information Theory?
Entropy in information theory is a measure of uncertainty. It tells us how surprised we are, on average, by the outcome of something, so low entropy means easy to guess.
How do Greedy Decoding and Beam Search differ?
Greedy Decoding and Beam Search differ in how many paths they keep while an LLM writes text. Greedy Decoding always picks the single best next word and never looks back, while Beam Search keeps a few of the best sentence options alive at every step and picks the best complete sentence at the end.
Why do sample rates like 8 kHz, 16 kHz, and 24 kHz matter for voice agents?
Sample rates like 8 kHz, 16 kHz, and 24 kHz matter for voice agents because the sample rate decides how much detail of a voice is kept, and every part of a voice agent expects audio at a specific sample rate. If we pick the wrong one, or mix them up, the agent hears worse, sounds worse, or breaks completely.
What is asked in a Voice AI Engineer interview?
A Voice AI Engineer interview tests whether we can build a real-time voice agent with a coding agent, verify it by placing a real call, and explain where the time goes between a person speaking and the agent replying.
How do WebRTC and WebSocket differ for voice AI agents?
WebRTC and WebSocket are two ways to carry live audio between a user and a voice AI agent. WebSocket sends every piece of audio over one reliable connection and waits for anything that is lost, while WebRTC is built for live voice, so it skips lost or late audio and keeps the conversation moving.
Do you need a degree or advanced math to become an AI Engineer?
No, you do not need a degree or advanced math to become an AI Engineer, because the job is about building products on top of existing models with a coding agent, and the math it uses is a small set that anyone can learn in a few weeks.