AI and Machine Learning Program
Software engineers like you join Outcome School AI and ML Program to achieve the outcome that is a high-paying tech job in AI and ML.
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 6 months. Simple explanations for complex topics.
6 months program
6 months long online learning program to master AI and Machine Learning.
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 in AI and ML, you must know the internals and be great at system design. Knowledge comes to those who crave for it.
Eligibility
Working tech professionals who want to learn AI from scratch and transition into high-paying AI roles through a strong understanding of AI, Machine Learning and System Design.
Prerequisite
Any programming language. Even without Python experience, if you know any other language, you can learn Python while building the projects.
Roles
With your effort, you can transition to
Curriculum
We will learn all of these in-depth:
- AI Engineering
- AI Engineering Overview
- LLM Fundamentals
- LLM Internals
- Tokenization
- Positional Encodings
- Q, K, V Matrices
- Attention Mechanism
- Self-Attention and Multi-Head Attention
- Causal Masked Attention
- Transformer Architecture
- KV Cache
- Paged Attention
- Speculative Decoding
- Continuous Batching
- Prompt Caching
- Mixture of Experts (MoE)
- Cross Attention
- Grouped Query Attention
- vLLM
- Prompt Engineering
- Prompt Chaining
- Chain of Thought (CoT) Prompting
- Context Engineering
- RAG
- Vector Databases
- Fine-tuning
- Parameter-Efficient Fine-Tuning (PEFT)
- Low-Rank Adaptation (LoRA), QLoRA
- Quantization and Optimizations
- Model Compression
- Knowledge Distillation
- SLMs and Model Distillation
- ReAct Pattern
- AI Agent
- Agentic AI
- Tool use in Agents
- Memory in Agents
- Model Context Protocol (MCP)
- Agent Architecture
- Subagent
- Multi-Agent Systems
- Orchestration and Routing
- Evaluation of LLMs and Agents
- LLM as a Judge
- Multimodal AI
- Build Your Own (From Scratch)
- Large Language Model (LLM)
- AI Tutor
- AI Coding Agent
- Neural Network
- AI and ML System Design
- Design ChatGPT: Training to Serving (End to End)
- Design a RAG System (Chat with Your Documents)
- Design Memory for a Personal AI Assistant
- Design a Deep Research Agent
- Design a Multi-Agent Customer Support System
- Design an On-Device AI Assistant
- Design a Multimodal Search System (Text, Image, Video)
- Design an LLM Inference Platform (vLLM-as-a-Service)
- Design an LLM Evaluation Platform
- Design a Text-to-Image Generation Service (Midjourney-like)
- Design a Music Generation Service (Suno-like)
- Design a Video Generation Service (Sora-like)
- Tools and Libraries
- PyTorch
- TensorFlow
- Keras
- Ollama
- Hugging Face
- LangChain
- LangGraph
- Data Analysis and Visualization
- NumPy
- Pandas
- Matplotlib, Seaborn
- Machine Learning Fundamentals
- Machine Learning Overview
- Supervised and Unsupervised Learning
- Self-supervised Learning, Contrastive Learning
- Linear Regression, Logistic Regression
- Gradient Descent
- Maths behind Gradient Descent
- Loss Functions
- Hyperparameter Tuning
- Epoch, Batch, Batch Size, and Iteration
- Embeddings
- Logits, Cross-Entropy
- Deep Learning
- Neural Networks
- Feed Forward Neural Networks (FFNNs)
- Activation Functions
- Backpropagation
- Dropout
- Layer Normalization and Batch Normalization
- Optimizers
- Generative AI
- Variational Autoencoders (VAEs)
- Autoregressive Models
- Diffusion Models
- Video Models
- Transformers
- Attention Mechanism
- Large Language Models (LLMs)
- Reasoning Models
- Encoder–Decoder Architecture
- Multimodal Generative Models
- Optimization and Scaling Techniques
- MLOps and LLMOps
- LLM Inference Optimization
- Data Management and Versioning
- Model Development and Training
- Evaluation and Testing
- Model Deployment and Serving
- Cloud vs On-device Deployment
- Monitoring and Logging
- Infrastructure and Platform
- Reinforcement Learning
- Exploration vs Exploitation
- Proximal Policy Optimization (PPO)
- Reward Models
- Direct Preference Optimization (DPO)
- Group Relative Policy Optimization (GRPO)
- RLHF (Reinforcement Learning from Human Feedback)
- Research Papers
- Attention Is All You Need
- Distilling the Knowledge in a Neural Network
Process
- 1
Watch the Demo Session Recording
Watch the demo session recording to see what you'll learn and how we break down the internal workings of complex concepts into simple, clear explanations. This video covers all the questions you may have.
- 2
Chat with us on WhatsApp to complete the enrollment
We'll understand your requirements and complete the enrollment process to get you started.
You'll chat with a real person. We've chosen NOT to integrate AI.
- 3
Attend Live Classes
We will be taking the live classes and teaching you the required concepts. You will also be interacting with the other students and learning from their experiences during the live classes.
- 4
Learn the Internals
You will go beyond using tools and libraries to understand how things actually work under the hood. By learning the internals, you build the deep understanding that sets you apart and makes you a stronger engineer. Along the way, you will also master the most important skill, debugging.
- 5
Learn System Design
System design is a key part of AI and Machine Learning interviews. Our students excel in system design interviews because they learn the right patterns, develop a strong product mindset, and think like true product engineers.
- 6
Profile and Resume building
You will build your profile(GitHub, LinkedIn) and resume. You will be open-sourcing your project on Github to create a better Github profile. Let the code show your skills to the world.
- 7
Mock Interviews
Mock interviews are very important before your real interviews. Students will be doing mock interviews with each other. You will get feedback to improve upon.
- 8
Learn how to apply to a company effectively
Learn how to apply to a company and get the interview call. We help with salary negotiation.
- 9
Company-Specific Interview Assistance
Have an upcoming interview? Reach out to learn what to prepare. If we find a student who has already given an interview at the same company, we share real interview insights.
- 10
Get a High-Paying Job
Finally, with your efforts, you will be able to get the job you desired.
Your 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
Amit Verma
I am immensely grateful to Amit Shekhar for his invaluable guidance and support in my journey as an Android developer. His clear and practical approach to teaching complex concepts made learning enjoyable and effective. With Amit's help, I am able to secure my dream job, and I continue to rely on his teachings as I advance in my career. I highly recommend Amit Shekhar to anyone looking to improve their development skills and achieve their professional goals. Thank you, Amit, for your support and for being an inspiring mentor and true leader!
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.
Aman Shekhar
I'm extremely grateful to Amit Shekhar for his guidance and support whenever I needed it. His teaching style made me feel very confident, as he has a unique ability to simplify complex topics. Amit's approach to teaching is what sets him apart. He also assisted me with mock interviews and preparation strategies for various companies. With his help, I successfully cracked interviews at multiple companies and currently hold a position as a Fullstack Engineer at Boeing. I highly recommend his program if you're looking to master system design.
Fee
The fee is updated for every batch. For the latest fee, please chat with our team on WhatsApp.
You'll chat with a real person. We've chosen NOT to integrate AI.
Frequently asked Questions
Why Outcome School AI and Machine Learning Program?
Software engineers like you join Outcome School AI and Machine Learning Program to get a high-paying job in AI and Machine Learning. In the live classes, we go deep into the internals of how things work and master system design, building the strong foundation that leads to a successful outcome.
What are the eligibility requirements for this program?
Working tech professionals who want to learn AI from scratch and transition into high-paying AI roles through a strong understanding of AI, Machine Learning and System Design.
What are the prerequisites?
Any programming language. Even without Python experience, if you know any other language, you can learn Python while building the projects.
Is the program completely online?
Yes
When can I join the program?
You can join it based on the slot availability.
What is the duration of this program?
6 months long online learning program.
What is the time commitment for the program?
We recommend spending an average of 5-10 hours per week. You can distribute these hours across the week according to your work schedule without missing the program’s goals.
What is the fee for this program?
The fee is updated for every batch. For the latest fee, please chat with our team on WhatsApp.
You'll chat with a real person. We've chosen NOT to integrate AI.