Guidetryb-3

From any background into Data Science!

Description:

The upcoming iteration of the Guidetryb course will be entirely centered around practical training. Our focus will be on the fundamental aspects of Data Science, preparing our mentees for their initial data science projects through hands-on experience sessions. We will begin by covering the basic toolkit necessary for practical tasks, such as the Python programming language and data visualization. Following this, we will delve into accomplishing statistical modeling using industry-standard packages. The latter half of the course will be devoted to more advanced topics, where we will explore the practical applications of cutting-edge machine learning algorithms and modern Neural Network architectures.

If you are not yet familiar with these topics, please do not worry. We will not delve into complex mathematical concepts, but instead, we will concentrate on practical applications.

The course will be delivered in 6 sessions, each 1.5-2 hours. After the session, students will be asked to complete homework based on lecture material.

Course outline:

1. Python basics. Libraries and modules essential for Data Science projects. [ipynb]
2. Exploratory data analysis (EDA) and data visualization with Python. [ipynb] [YouTube]
3. Basic statistics concepts with Python. [ipynb] [YouTube]
4. Linear regression. [ipynb] [YouTube]
5. Regression problem ML projects structure. [ipynb] [YouTube]
6. Classification problem ML projects structure. [ipynb] [YouTube]
7. Basics of Neural Networks and Computer Vision models.
8. CVs review and Interview preparation.

Home works

1. Basic python. [pdf]
2. Pandas data manipulations. [ipynb]
3. ML project. [ipynb]

This version of course completely reworked, and we will have 90% of practical programming session.