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Intermediate Level: Machine Learning With Python

SAT Score Range

14 sessions

+3

This series ended on May 1, 2025. All 1:1 and group chats related to this series are disabled 7 days after the last session.

About

Focus: Deep Learning, CNNs, Transfer Learning, Tuning, Dimensionality Reduction, Deployment

Hello, my name is Rohan! I have experience with machine learning, and I have conducted multiple research projects on the subject. This course is intended for intermediate students who want to learn more about Python and machine learning.
Sessions and times are flexible, so please message me if you want to change dates/times. It is recommended to have brief Machine Learning and Python experience, but I will be doing a quick rundown in the introductory session. I hope to see you there!

P.S: If you were a part of the 'Introduction to Machine Learning with Python' series, I would HIGHLY recommend joining this, as we are going to the next level! :)

Tutored by

Rohan A 🇺🇸

Senior Tutor

Certified in 40 topics

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Hello, my name is Rohan! I am from New Jersey, and I am currently a high schooler. My goal on Schoolhouse is to help other students like me learn and be prepared for anything. My passion lies in machine learning (ML), and I have researched many topics of machine learning! (I have two publicly accessible research papers). Additionally, I enjoy software engineering on a broader level, with interests in competitive programming (I am a USACO Silver Competitor) and web development. During my free time, I am an avid videogame player, with multiple Platinum trophies on difficult "souls" games. I have also played piano for 6 years and arrange my favorite video game tracks on piano (like "Escaping a Foul Prescence" from Ori 2, "Abyss Watchers" from Dark Souls 3, and "Final Battle" from Elden Ring as great examples)! Going outside the house, I play goalkeeper for my high school soccer team and I am a varsity swimmer. In addition to computer science, I also love mathematics, so if you have any questions about any High School Mathematics, Machine Learning, Python, or Java, feel free to ask me and I will try to get back to you with answers! Happy learning everyone! - Rohan

Schedule

✋ ATTENDANCE POLICY

Please let me know if you cannot make a session.

SESSION 1

18

Apr

SESSION 1

Artificial Intelligence

Artificial Intelligence

Fri 12:00 AM - 1:00 AM UTCApr 18, 12:00 AM - 1:00 AM UTC

Lesson 1: Recap of Preliminary Material

  • Python Basics
  • Data Basics
  • What is a Machine Learning Model?
  • Classification v/s Regression
SESSION 2

19

Apr

SESSION 2

Artificial Intelligence

Artificial Intelligence

Sat 12:00 AM - 1:00 AM UTCApr 19, 12:00 AM - 1:00 AM UTC

Lesson 2: Data Preprocessing & Feature Engineering

  • Normalization, scaling
  • Encoding categorical variables
  • Handling missing values
  • Creating new features
SESSION 3

20

Apr

SESSION 3

Artificial Intelligence

Artificial Intelligence

Sun 12:00 AM - 1:00 AM UTCApr 20, 12:00 AM - 1:00 AM UTC

Lesson 3: Neural Networks & Deep Learning Fundamentals

  • Perceptrons, hidden layers, weights
  • Forward and backpropagation
  • Overfitting vs underfitting in deep learning
SESSION 4

21

Apr

SESSION 4

Artificial Intelligence

Artificial Intelligence

Mon 12:00 AM - 1:00 AM UTCApr 21, 12:00 AM - 1:00 AM UTC

Lesson 4: Activation Functions & Loss Functions

  • Sigmoid, ReLU, Softmax
  • Loss functions: MSE, Cross-Entropy
  • Role in optimization


SESSION 5

22

Apr

SESSION 5

Artificial Intelligence

Artificial Intelligence

Tue 12:00 AM - 1:00 AM UTCApr 22, 12:00 AM - 1:00 AM UTC

Lesson 5: Convolutional Neural Networks (CNNs)

  • Filters, pooling, feature maps
  • How CNNs work for image data
  • Simple image classification example
SESSION 6

23

Apr

SESSION 6

Artificial Intelligence

Artificial Intelligence

Wed 12:00 AM - 1:00 AM UTCApr 23, 12:00 AM - 1:00 AM UTC

Lesson 6: Advanced Evaluation Metrics

  • Precision, Recall, F1-Score
  • Confusion Matrix deep dive
  • ROC-AUC, PR Curves
  • For classification + regression
  • 

SESSION 7

24

Apr

SESSION 7

Artificial Intelligence

Artificial Intelligence

Thu 12:00 AM - 1:00 AM UTCApr 24, 12:00 AM - 1:00 AM UTC

Lesson 7: Model Optimization & Tuning

  • Grid Search, Random Search
  • Hyperparameter tuning
  • Epochs, batch size, learning rate
SESSION 8

25

Apr

SESSION 8

Office Hours

Office Hours

Fri 12:00 AM - 1:00 AM UTCApr 25, 12:00 AM - 1:00 AM UTC

MIDTERM REVIEW: Practice / Recap Session

  • Recap CNNs, metrics, tuning
  • Mini project or Kahoot review
  • Open Q&A


SESSION 9

26

Apr

SESSION 9

Artificial Intelligence

Artificial Intelligence

Sat 12:00 AM - 1:00 AM UTCApr 26, 12:00 AM - 1:00 AM UTC

Lesson 8: Dimensionality Reduction & Visualization

  • PCA, t-SNE, UMAP
  • Visualizing high-dimensional data
  • Reducing noise & improving speed
SESSION 10

27

Apr

SESSION 10

Artificial Intelligence

Artificial Intelligence

Sun 12:00 AM - 1:00 AM UTCApr 27, 12:00 AM - 1:00 AM UTC

Lesson 9: Transfer Learning

  • What is it? Why is it powerful?
  • Using pretrained models (e.g., VGG16, ResNet)
  • Fine-tuning vs freezing layers


SESSION 11

28

Apr

SESSION 11

Artificial Intelligence

Artificial Intelligence

Mon 12:00 AM - 1:00 AM UTCApr 28, 12:00 AM - 1:00 AM UTC

Lesson 10: Working with Imbalanced Data

  • Upsampling, downsampling
  • SMOTE
  • Adjusting evaluation strategy for skewed classes
SESSION 12

29

Apr

SESSION 12

Artificial Intelligence

Artificial Intelligence

Tue 12:00 AM - 1:00 AM UTCApr 29, 12:00 AM - 1:00 AM UTC

Lesson 11: Model Deployment Basics

  • Exporting models (.pkl, h5)
  • Flask/FastAPI introduction
  • Deployment strategy overview (local vs cloud)
SESSION 13

30

Apr

SESSION 13

Artificial Intelligence

Artificial Intelligence

Wed 12:30 AM - 1:30 AM UTCApr 30, 12:30 AM - 1:30 AM UTC

Lesson 11: Model Deployment Basics
- Exporting models (.pkl, .h5)
- Flask/FastAPI intro
- Deployment strategy overview (local vs cloud)

SESSION 14

1

May

SESSION 14

Office Hours

Office Hours

Thu 12:30 AM - 1:30 AM UTCMay 1, 12:30 AM - 1:30 AM UTC

Recap day. I will have summaries of every lesson.

Public Discussion

Please log in to see discussion on this series.

Apr 18 - May 1

2 weeks

60 mins

/ session

SCHEDULE

Fridays

12:00AM

Saturdays

12:00AM

Sundays

12:00AM

Mondays

12:00AM

Tuesdays

12:00AM