course
Machine Learning
Get real experience by solving practical tasks using machine learning!
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Course programme
In the machine learning course you will get real experience in solving practical problems using data analysis tools!
Required skills for the course : knowledge of Python
1
Introduction
Basic concepts of machine learning, Python for data analysis
2
Classification
Classification problem, metrics, non-parametric methods, linear classifiers, logical methods: decision trees, Naive Bayes classifier
3
Regression recovery
Metrics, problem statement, classification models that can be used for regression, linear algorithms
4
Ensemble
Bagging, Random Forest, boosting, stacking
5
Feature engineering
Work with features
6
Clustering tasks
Clustering
7
Work on a commercial project
Methodology of solving a problem with a teacher (crisp dm) and Real case (prediction and outflow clustering)
Skills, that you will acquire
1
Machine learning skills
- Knowledge of machine learning algorithms and understanding of the principles of their work
- Mastering the methodology of working with data
- Ability to lead a project from start to finish
2
Knowledge of data analysis tools
- Mastering modern methods and tools for analysing and processing data
- Ability to extract valuable information from large data sets and use it effectively
3
Ability to build models for solving business cases
- Computer vision
- HR analyst
- Scoring
- Audio and video analytics
Experts
Our experts will help you to become a data scientist
Dmitriy
Luppov
Technical director of the company "ChatMe", Data Scientist. Works on challenging tasks in the areas of classical machine learning, Deep Learning and Natural Language Processing. Conducted several courses on machine learning / data analysis / artificial intelligence in Russia and Kazakhstan.
Aleksandr
Zyranov
Lead Data Scientist in "Expasoft".
Expert skills in Python, SciPy Stack, Sklearn, Seaborn, TensorFlow, Keras, Torch, NLTK, spaCy, gensym.
Alexander worked on following projects: Face Recognition (based on Convolution neural networks and deep learning), brand detection and recognition (Deep Learning), machine learning for bank transactions monitoring (TOP-10 Russian banks), credit scoring model, online traffic user classification, training courses in machine learning.

Aleksandr
Polygalov
Data Scientist in "Expasoft".
Expert skills in Python, Tensorflow, Keras, openCV, machine learning, computer vision, predictive analytics, data analysis.
Has scholarships from Schlumberger, British Petroleum, Baker Hughes.
Won 1st place in the online part of PicsArt AI 2018 - Computer Vision solution for portrait segmentation, 2nd place at Venture Day Minsk 2018, Minsk.
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