03/01/2021
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Programming course (Machine learning and data analysis in Python), 9th grade - course RUB 31,250. from Foxford, training, Date: December 4, 2023.
Miscellaneous / / December 04, 2023
Who will benefit from the course?
The course will be useful for those who have already studied the basics of programming and want to expand their area of knowledge, plunge into Data Science, and understand what neural networks and artificial intelligence are.
What knowledge does the course provide?
Confident knowledge of Python and the main libraries for DS, ability to work with machine learning algorithms for classification and regression problems, practical experience in participating in competitions on this topic.
How the training works
Under the guidance of a teacher, the children will participate in real machine learning competitions for adults. The course will include online meetings with representatives of the IT industry.
School certification
Each lesson has a plot and interactive tasks.
We know how to approach children
Available in recording
Compliance
You will gain basic knowledge of the subject
Our teachers are participants in competitions, authors of methodological developments
They know how to interest every child, taking into account age characteristics. Each lesson is an exciting journey into the World of Knowledge!
Let's look at the main topics of the program
The child will not have to study the material on his own and cram it without understanding. The teacher will explain even complex topics in simple language, and presentations and interactive tasks will increase interest in the subject.
Let's consolidate knowledge in practice
After each lesson, a small homework task that will help you practice the material covered and practice before the test.
We manually check samples and homework
We do not leave the written part assignments for self-testing - this is done by OGE experts.
We check “for real”, like in an exam, and as a result you receive detailed feedback. All this is for the sake of speed of preparation and your results. Your personal curator will answer your questions within two hours, 24/7
The curators understand the program and the subject, so they can easily answer your questions about the course and homework - at any time
They know well how difficult it can be to prepare and understand your worries.
The most important task of a tutor is to help you cope with stress and fear before exams
Python Basics (Review, Quick Review)
- Basic Python control constructs
- Functions
- Lists
- Object-oriented programming
Introduction to Libraries for Data Science
- Numpy
- Matplotlib
-Random
- Pandas
- Seaborn
- Sklearn
Introduction to Machine Learning
- Basics of linear algebra. scipy library. Loss functions
- Linear regression and classification algorithms
- Setting up models: retraining, regularization, selection of hyperparameters, quality metrics
- Random trees
- Compositions of algorithms: bagging and random forest
- Competitions on kaggle
- Unsupervised learning: clustering, dimensionality reduction
Data Analysis in Practice
- Confidence intervals, hypothesis testing
- A/B - testing
- Statistical criteria
- Search for patterns and dependencies in data
- Time series forecasting
- Competitions on kaggle
Deep learning
- Introduction to neural networks. DL and AI tasks
- Construction of a multilayer perceptron
- Derivative and gradient. Gradient Descent Methods
- Setting up neural networks: selection of hyperparameters, softmax, partitioning into batches
- Introduction to the pytorch framework
- Fundamentals of Convolutional Neural Networks
- CNN architectures. Transfer learning
- Computer vision tasks: image segmentation and detection
- Selected NLP tasks. Competitions on kaggle
- Generating artificial data using GAN
- The Data Scientist's Way
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