Amazon ML Summer School 2025: How to Apply, Prepare, and Get Selected
The Amazon Machine Learning (ML) Summer School is a transformative program designed to equip engineering students in India with cutting-edge machine learning skills, preparing them for thriving careers in this rapidly evolving field. Launched in 2021, the fifth edition of this prestigious program in 2025 promises an immersive learning experience led by Amazon’s top scientists. This blog covers everything you need to know about the Amazon ML Summer School 2025, including what it is, who can apply, how to apply, a preparation guide, and insights into past questions and program benefits.
What is the Amazon ML Summer School?
The Amazon ML Summer School is a free, intensive educational program aimed at fostering machine learning expertise among engineering students in India. Running over four weekends from August 9 to August 31, 2025, the program combines theoretical foundations with practical applications, delivered by Amazon’s expert scientists. It covers critical ML topics such as Supervised Learning, Deep Neural Networks, Generative AI, Reinforcement Learning, and more, ensuring participants are industry-ready.
Key Features:
- In-Depth Curriculum: Eight modules covering topics like Supervised Learning, Deep Neural Networks, Probabilistic Graphical Models, Dimensionality Reduction, Unsupervised Learning, Sequential Models, Reinforcement Learning, Generative AI, and Causal Inference.
- Interactive Learning: Each module includes a four-hour session (9:00 AM–1:00 PM IST), a one-hour break, and a three-hour live Q&A with Amazon scientists (2:00 PM–5:00 PM IST).
- Networking Opportunities: Engage with Amazon scientists and attend the Amazon Research Days (ARD) conference to connect with global AI/ML leaders.
- Career Prospects: Top performers can apply for internships in Data Science or Applied Scientist roles at Amazon, with opportunities for hands-on experience in cutting-edge projects.
Since its inception, the program has seen massive interest, with over 17,500 registrations in 2022 and thousands participating annually. It’s a unique platform to bridge the gap between academic learning and industry demands, as highlighted by Rajeev Rastogi, Vice President of Applied Science: “This program will be a platform to help foster ML excellence and strive towards developing applied science skills in young talent.”
Who Can Participate?
The Amazon ML Summer School 2025 is open to engineering students across India who meet the following eligibility criteria:
- Academic Level: Enrolled in a Bachelor’s, Master’s, or PhD program at any recognized institute in India.
- Graduation Year: Expected to graduate in 2026 or 2027.
- Background: Open to students from any engineering discipline. While prior knowledge of programming (especially Python) and basic ML concepts is beneficial, no specific branch or prior ML experience is required.
What is the Selection Criteria?
The selection test for the Amazon ML Summer School 2025 is designed to evaluate candidates’ foundational knowledge and problem-solving skills. It consists of two parts:
Part A: 20 multiple-choice questions (MCQs) on basic ML concepts and math fundamentals, covering topics such as probability (e.g., Bayes’ theorem, expected value), statistics (e.g., mean, variance, hypothesis testing), and linear algebra (e.g., matrix operations, eigenvalues).
Part B: Two programming questions, typically medium-level data structures and algorithms (DSA) problems, solvable in any programming language (Python recommended). Examples include problems like finding non-overlapping intervals or computing medians in a data stream.
Duration: The test lasts 60 minutes, requiring efficient time management.
Selection Process: The top 3,000 performers in the test are shortlisted for the program.
How to Apply: A Step-by-Step Guide
The application process for the 2025 Amazon ML Summer School is straightforward but competitive. Here’s how to apply:
- Register by July 31, 2025:
- Visit the official Amazon ML Summer School application portal
- Complete the registration form with your academic details, programming skills, and interest in ML.
- Direct application link
- Selection Test on August 3, 2025:
- Eligible applicants must take an online assessment, typically conducted on platforms like HackerRank or Mercer-Mettl.
- The test has two parts:
- Part A: 20 multiple-choice questions (MCQs) on basic ML concepts and math fundamentals (probability, statistics, linear algebra).
- Part B: Two programming questions, typically medium-level data structures and algorithms (DSA) problems, solvable in any language (Python recommended).
- Duration: 75 minutes.
- Key Topics:
- ML: Supervised/unsupervised learning, regression, classification, gradient descent, decision trees.
- Math: Probability (e.g., Bayes’ theorem), statistics (e.g., mean, variance), linear algebra (e.g., matrix operations).
- Programming: Arrays, linked lists, priority queues, or problems like finding medians or non-overlapping intervals.
- Test Tips:
- Practice for mock test from here – Lets Code
- You cannot change your test slot once selected.
- Start the test within the designated slot; accidental test termination may disqualify you.
- Sample tests may be available on the platform to understand the difficulty and pattern.
- Shortlisting by August 7, 2025:
- The top 3,000 performers in the selection test will be shortlisted and notified via email.
- Check your email (including spam/junk folders) for confirmation and program access details.
- Program Starts on August 9, 2025:
- Attend virtual sessions over four weekends (August 9–10, 16–17, 23–24, 30–31).
- Engage in interactive lectures, hands-on assignments, and Q&A sessions with scientists like Anil Kumar N, Aadil Hayat, and Prakash M Comar.
- Post-Program Opportunities:
- Complete an interest form for internships in Data Science or Applied Scientist roles.
- Shortlisted candidates may undergo additional coding tests (e.g., LeetCode hard-level problems) and interviews.
Program Schedule
The 2025 Amazon ML Summer School will run over four weekends, with each day featuring:
- Module Session (9:00 AM–1:00 PM IST): In-depth lectures on ML topics.
- Break (1:00 PM–2:00 PM IST): Time to reflect and prepare for Q&A.
- Live Q&A with Scientists (2:00 PM–5:00 PM IST): Interactive discussions with Amazon experts.
2025 Schedule:
- August 9: Module 1
- August 10: Module 2
- August 16: Module 3
- August 17: Module 4
- August 23: Module 5
- August 24: Module 6
- August 30: Module 7
- August 31: Module 8
The virtual format ensures accessibility for students across India, with no registration or course fees.
Preparation Guide: Tips for Success
To secure a spot in the Amazon ML Summer School 2025 and maximize your learning, follow these preparation strategies:
1. Master the Basics
- ML Concepts:
- Study supervised and unsupervised learning, regression, classification, decision trees, gradient descent, and evaluation metrics (e.g., accuracy, precision).
- Resources: “Introduction to Machine Learning” by Ethem Alpaydin, Coursera’s Machine Learning by Andrew Ng, or Fast.ai courses.
- Mathematics:
- Focus on probability (e.g., conditional probability, expected value), statistics (e.g., hypothesis testing, variance), and linear algebra (e.g., matrix multiplication, eigenvalues).
- Resource: Khan Academy’s linear algebra and statistics courses.
- Programming:
- Be proficient in Python, including libraries like NumPy, pandas, and scikit-learn.
- Practice DSA problems on LeetCode, HackerRank, or GeeksforGeeks, focusing on arrays, linked lists, priority queues, and problems like “Non-overlapping Intervals” or “Find Median from Data Stream.”
2. Practice Past Questions (PYQs)
While exact past questions are not publicly available, insights from previous years highlight common themes:
- MCQs:
- Probability: Bayes’ theorem, expected value.
- Statistics: Mean, median, mode, hypothesis testing.
- Linear Algebra: Matrix operations, determinants, vector spaces.
- ML Basics: Overfitting, regularization, gradient descent, decision trees.
- Example: “What is the effect of regularization on model complexity?”
- Programming Questions:
- Example 1: “Sort a list of prime and non-prime orders” (similar to LeetCode’s array-based problems).
- Example 2: “Find the shortest path from source to destination” or priority queue problems like finding medians in a stream.
- Difficulty: Easy to medium, solvable within 30–40 minutes.
- Practice Resources:
- GitHub repository cu-sanjay/Amazon-ML-Summer-School-2024 for sample MCQs and coding problems.
- LeetCode problems tagged with arrays, dynamic programming, or priority queues.
- GeeksforGeeks for ML and DSA practice.
3. Resources
- Books: “Deep Learning” by Ian Goodfellow, “Pattern Recognition and Machine Learning” by Christopher Bishop.
- Online Courses: Scaler Academy (Amazon’s partner), Coursera, edX, or Fast.ai for ML fundamentals.
- Blogs and Forums: Check Reddit’s r/learnmachinelearning for participant tips or Amazon Science blogs for program insights.
- Coding Platforms: Practice on HackerRank or LeetCode to simulate the test environment.
4. Prepare for the Test
- Time Management: Allocate ~30 minutes for MCQs and ~45 minutes for coding questions in the 75-minute test.
- Python Proficiency: Use Python for its simplicity and relevance to ML tasks.
- Edge Cases: Test your code for boundary conditions (e.g., empty arrays, large inputs).
- Sample Tests: Check the application portal for sample tests to gauge difficulty and familiarize yourself with the format.
5. Engage During the Program
- Actively participate in Q&A sessions to clarify concepts and network with scientists.
- Complete assignments to reinforce learning and demonstrate commitment.
- Prepare for the Amazon Research Days (ARD) conference to connect with global ML leaders.
Why Join the Amazon ML Summer School?
- Industry-Relevant Skills: Learn from Amazon scientists who apply ML to real-world problems, such as improving product recommendations or optimizing delivery systems.
- Career Opportunities: Top performers may secure internships or full-time roles at Amazon. For example, Prabash Male, a 2022 participant, became an Applied Scientist at Amazon, crediting the program for his career growth.
- Networking: Build connections with Amazon scientists and peers, enhancing your professional network.
- Free Access: No registration or course fees, making it accessible to all eligible students.
- Practical Focus: The program’s blend of theory and hands-on exercises aligns with industry needs, as noted by Vineet Chaoji, Director of Machine Learning: “The modules will supplement coursework and help students better prepare for solving practical problems in the industry.”
Success Stories
Participants have praised the program’s impact:
- A 2024 participant shared on GeeksforGeeks: “The structured learning and interaction with experts made it an unforgettable experience. It enriched my skills and fueled my passion for AI.”
- Another student secured a six-month internship at Amazon after the 2023 program, attributing their success to the mentorship and practical training received.
Conclusion
The Amazon ML Summer School 2025 is a golden opportunity for engineering students in India to master machine learning under the guidance of Amazon’s top scientists. With a rigorous selection process, a comprehensive curriculum, and unparalleled career prospects, this program is a stepping stone to a successful ML career. Start preparing now by honing your ML, math, and coding skills, and mark your calendar for the July 31, 2025, application deadline. For more details, visit Amazon Science or follow updates on platforms like Unstop or Mercer-Mettl.
Invest in your future—apply today and take the first step toward becoming an ML expert!
Join Telegram group for discussion!
🧰 Useful Resources for Your Placement Prep
Lets Code
Contributing Writer