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Not enrolling any more students for 2025
Machine Learning
for High School Students
🎯 Learn Machine Learning, Deep Learning and Generative AI
concepts using First Principles
🎯 Work on tons of practice material and quizzes
🎯 Boost your college application!
📅 June - August, 2025
🧑🏫 In-person
(@ 100 S Murphy Ave, STE 200, Sunnyvale, CA)
💰 $1,499 (apply by April 15, 2025)
🎁 Parents are also welcome to enroll for $599
8-week Curriculum
8-week Curriculum
Week 1: ML Basics
Conceptual Learning + Quiz:
Supervised Learning
Unsupervised Learning
Applications of ML in industry
Hands-on Learning + Student Presentations:
Intro to Numpy, Matplotlib
Data Exploration
Homework:
Practical use cases
Week 2: Linear Regression
Conceptual Learning + Quiz:
Data Cleaning and Preparation
Derivation of Linear Regression
Regression Evaluations
Hands-on Learning + Student Presentations:
Data Preparation
Regression Applications
Homework:
Practical use cases
Week 3: Classification
Conceptual Learning + Quiz:
Derivation of Logistic Regression
Gradient Descent
Classification Evaluations
Hands-on Learning + Student Presentations:
Classification Applications
Imbalanced Class problems
Homework:
Practical use cases
Week 4: Non-Linear Classifiers
Conceptual Learning + Quiz:
Support Vector Machines (SVM)
Ensemble Models: Decision Trees, Random Forest and Boosting
Hands-on Learning + Student Presentations:
Performance comparison with Linear Classifiers
Homework:
Practical use cases
Week 5: Model Evaluation
and Selection
Conceptual Learning + Quiz:
Cross-Validation
Hyper-parameter Optimization
Model Selection
Hands-on Learning + Student Presentations:
Performance comparison of different classifiers
Homework:
Practical use cases
Week 6: Unsupervised Learning
Conceptual Learning + Quiz:
Clustering: K-means, Hierarchical Clustering
Dimensionality Reduction: PCA, LDA
Hands-on Learning + Student Presentations:
Clustering Applications
Recommendation Applications
Homework:
Practical use cases
Week 7: Deep Learning
Conceptual Learning + Quiz:
Feed-Forward Neural Networks
Optimization Methods of Deep Learning models
Hands-on Learning + Student Presentations:
Image Classification
Comparison of DL models with traditional models
Homework:
Practical use cases
Week 8: Generative AI
Conceptual Learning + Quiz:
Large Language Models and Transformers
Prompt Design and API Integration
Hands-on Learning + Student Presentations:
Intelligent Agents
LLM Fine-tuning
Homework:
Practical use cases
Teaching Approach
Teaching Approach
Algorithms are explained using First Principles and High School-level math
Algorithms are explained using First Principles and High School-level math
Machine Learning is all about problem solving. Most machine learning algorithms can be simplified into basic postulates and can be derived using logical reasoning and high school-level math.
These simplified derivations allow students to easily understand the intricate workings of the algorithms and appreciate their use cases.
Learn how to debug and optimize Machine Learning algorithms
Learn how to debug and optimize Machine Learning algorithms
Hypothesize which algorithm to use when, build intuition on how an algorithm should perform, and learn how to debug an algorithm to squeeze every last bit of performance.
This is probably the most important aspect of Machine Learning that takes researchers years to master!
Tons of Hands-on Practice Material
Tons of Hands-on Practice Material
Every lecture will be accompanied by hands-on practice sessions, where students will work on real-life applications of Machine Learning. The practice sessions will also include quizzes, competitions and will conclude with presentations from the students.
This will help students cement their understanding of the concepts discussed during the lecture.
Ignite the spark for problem solving and Innovation
Ignite the spark for problem solving and Innovation
In Machine Learning, there is no one-size-fits-all solution. Every problem requires nuanced thinking and a unique approach to problem solving.
Real-world scenarios combined with interactive learning experiences, will help ignite the spark for innovation in students and will encourage them to think creatively as they learn the skills of the future.
Apply Now:
Apply Now:
Application Deadline:
Apply by April 15, 2025: $1,499
Frequently Asked Questions
Frequently Asked Questions
About the Program
About the Program
Q. Why should I join the MLCamps Education program?
Q. Why should I join the MLCamps Education program?
You should join the program:
If you are fascinated by the world of Machine Learning, this might be a perfect opportunity for you to explore what the field of AI/ML entails, the power of AI in solving the world's problems, the science behind it, and the approach to problem solving.
If you want to pursue a college degree in Computer Science, Machine Learning or related field, this will give you a head start and a solid experience to boost your profile in the college application
If you want to explore the use of AI/ML in your field of interest be it art, literature, fashion or sociology. In the coming future, the application of machine learning is going to be universal, and the use of AI indispensable across industries
If you are curious what AI/ML buzz is all about
If you want to network with like-minded individuals and form a peer group for support and collaboration
Q. How does MLCamps differentiate itself from other similar Summer programs?
Q. How does MLCamps differentiate itself from other similar Summer programs?
You learn from the best Machine Learning talent in the industry. What differentiates us from other Summer programs is the intellectual and industrial experience of our instructors.
Our instructors are PhDs in Machine Learning, individually having 10+ years of industry experience working for FAANG companies. With this decade long experience, our instructors have practically seen all types of problems that crop us when building machine learning solutions and know the elixir to solving those problems. They know what it takes to become a good machine learning scientist and are passionate about teaching the same to students.
With ~30 hours of instructor-led training, our MLCamp will be an immersive experience for the students learning the breadth and depth of Machine Learning - a field that's reshaping the future.
Q. When are the applications due?
Q. When are the applications due?
We are accepting applications for Summer 2025. Application deadline is March 31, 2025
Q. I just graduated from high school. Can I apply to this program?
Q. I just graduated from high school. Can I apply to this program?
Definitely. We believe that this is a great program for anyone who is curious and wants to learn about Machine Learning
Q. What is the refund or cancellation policy?
Q. What is the refund or cancellation policy?
You may cancel for a full refund (minus $100 administrative fee) until April 30th, 2025
Q. Do you have a referral program?
Q. Do you have a referral program?
Yes, we do have a referral program as stated below:
Refer your friends and earn $50 reward for every student who enrolls in the program. Your friend also get a reward of $50. Your friend must put your name under the referral section while applying
Referral bonuses will be disbursed after the 2nd session via Amazon gift cards
Only enrolled students are eligible to earn the referral bonus.
Program Logistics
Program Logistics
Q. What does the Summer Camp schedule look like?
Q. What does the Summer Camp schedule look like?
There will be 8 sessions in total. These sessions will be held once a week. Summer camp will commence from June 15, 2025 and will conclude on August 10, 2025
In-Person sessions will be held every Sunday from 9a - 12:30p PST at Downtown, Sunnyvale (100 S Murphy Ave, Ste 200).
August 16 and 17, 2025 are Makeup days, to help students makeup for any of the sessions that they might have missed.
*There are no classes scheduled for the July 4th long weekend
Q. I will be traveling for a couple of weeks during summer. Will there be makeup sessions?
Q. I will be traveling for a couple of weeks during summer. Will there be makeup sessions?
Yes, we understand that people might have travel plans during summer. Therefore, we have reserved August 16 and 17 as Makeup days to help students cover up for any sessions that they might have missed.
Q. Do I need to have coding experience to enroll in this program?
Q. Do I need to have coding experience to enroll in this program?
Students are expected to have a basic knowledge of Python. Instructors will cover Numpy and other required libraries during the first session.
Q. Do I need any advanced math knowledge for this program?
Q. Do I need any advanced math knowledge for this program?
High school level math knowledge is sufficient for this program.
Q. Is the program in-person or virtual?
Q. Is the program in-person or virtual?
We offer only In-Person sessions. We strongly believe that the quality of learning is much better in in-person classes than virtual sessions.
Q. Are there any take-home assignments or homework associated with this program?
Q. Are there any take-home assignments or homework associated with this program?
There will be optional homework assignments. These homeworks are aimed at helping students think independently and derive solutions on their own. The correct solution to the homeworks will be discussed in the following lecture.
Post Completion
Post Completion
Q. Will I get a certificate for completing this program?
Q. Will I get a certificate for completing this program?
Yes, we will provide a certificate upon the completion of the program.
Q. Can I seek advice on future career paths in Machine Learning or college admissions?
Q. Can I seek advice on future career paths in Machine Learning or college admissions?
Absolutely. Our instructors are there to help you every step of the way and you are free to ask them questions on future career paths and college admissions.
Q. Can I get recommendation letter in future if needed?
Q. Can I get recommendation letter in future if needed?
You may certainly reach out to us for a recommendation letter. It will be provided on the discretion of the Program Director.
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