Machine Learning / AI Engineer in English
Идет набор
Duration: 6 months
Стажировка на коммерческом проекте в США
Мы учим владеть AI инструментами. Именно таких специалистов ищут компании.
Помогаем составить резюме и тренируем прохождение собеседований.
Стажировка на реальных проектах в команде.
Где работают наши выпускники
В этих известных компаниях наши студенты работают на фултайм и контракте. А также огромное количество выпускников трудится в сотнях других компаний по всему миру.
Средняя зарплата по уровням
Ваш карьерный путь от первой работы до эксперта. Зарплаты актуальны для рынка США на 2025 год.
$0
Обучение и практика
в PASV
в PASV
$35 000 — средняя американская зарплата
$90 000
Первая работа
1 год
$140 000
Рост
2 года
$180 000
Профессионал
3 года
$250 000 +
Эксперт
4+ года
Отзывы выпускников курса Machine Learning / AI Engineer in English
Студенты начинают проходить собеседования еще во время курса. Все наши студенты, кто выходит на поиск работы получает работу в течение 1-2 месяцев поиска.
О профессии
Machine Learning Engineers and Data Scientists are responsible for disigning, building, testing, and updating AI and machine learning systems and technologies. Machine learning is an evolving branch of computational algorithms that are designed to emulate human intelligence by learning from surrounding environment.They are considered the working horse in the new era of so-called big data. Techniques based on machine learning have been applied successfully in diverse fields ranging from pattern recognition, computer vision, spacecraft engineering, finance, entertainment, and computational biology to biomedical applications.
Что вы получите по окончании
- Understanding, analyzing, and applying machine learning principles for reasoning processes and uncertainty
- Utilizing machine learning to perform image analysis and reconstruction tasks
- Solving a variety of complicated problems and scenarios by implementing machine learning and AI-driven solutions
- Designing and building machine learning and AI-based solutions to perform complex tasks that model and improve upon typical human behavior
- Devising and building complex problem-solving solutions that use machine learning principles and AI best practices
- Spouses can study on the same course together at the same price!
Кому подойдет этот курс
Программа курса
Introduction to Data Science
Linear Regression & Introduction to “sklearn” library
Simple Linear Regression
Multiple Linear Regression
Linear Regression with categorical variables
Ridge and Lasso Regression
Assignment
Multiple Linear Regression
Linear Regression with categorical variables
Ridge and Lasso Regression
Assignment
Introduction to machine learning
K-Nearest Neighbors & Cross-Validation
Model validation is very simple: after choosing a model and its hyperparameters, we can
estimate how effective it is by applying it to some of the training data and comparing the
prediction to the known value.
This is a naive approach to model validation and why it fails,
before exploring the use of holdout sets and cross-validation for more robust model evaluation.
estimate how effective it is by applying it to some of the training data and comparing the
prediction to the known value.
This is a naive approach to model validation and why it fails,
before exploring the use of holdout sets and cross-validation for more robust model evaluation.
Stock Market Prediction
Stock price and volatility forecasting
Principal Components Analysis and Regression
PCA is fundamentally a dimensionality reduction algorithm, but it can also be useful as a tool for visualization, noise filtering, feature extraction and engineering, and much more.
Principal Components Analysis
Principal Components Regression
Principal Components Logistic Regression
Visualizing Principal Components Analysis
Principal Components Analysis
Principal Components Regression
Principal Components Logistic Regression
Visualizing Principal Components Analysis
K-means clustering
The k-means algorithm searches for a predetermined number of clusters within an unlabeled
multidimensional dataset. It accomplishes this using a simple conception of what the optimal clustering looks like: The cluster center is the arithmetic mean of all the points belonging to the cluster.
multidimensional dataset. It accomplishes this using a simple conception of what the optimal clustering looks like: The cluster center is the arithmetic mean of all the points belonging to the cluster.
Classification
We will illustrate the concept of classification using the simulated Default data set.
We are interested in predicting whether an individual will default on his or her credit card payment, on the basis of annual income and monthly credit card balance.
Logistic Regression
Generative models for classification
Generalized Linear Models
We are interested in predicting whether an individual will default on his or her credit card payment, on the basis of annual income and monthly credit card balance.
Logistic Regression
Generative models for classification
Generalized Linear Models
Tree based methods
Basics of decision trees
Sklearn documentation: Decision Trees
Random forests
Sklearn documentation: Decision Trees
Random forests
Predicting Student Loan Prepayment
Student Loan: Overfitting
Student Loan: Alternative Metric & Cross-Validation
Student Loan: Hyperparameter Tuning
Student Loan: xgboost
Project: student_loan
Student Loan: Alternative Metric & Cross-Validation
Student Loan: Hyperparameter Tuning
Student Loan: xgboost
Project: student_loan
Data Cleaning
Support Vector Machines
Maximal Margin Classifier
Support Vector Classifier
Support Vector machines
SVM with more than 2 classes
Support Vector Classifier
Support Vector machines
SVM with more than 2 classes
Neural Networks
MNIST Digit Recognition
Student Loan: Neural Network
Exchange Rate Prediction
Stock Returns: Neural Network
Numerai
Exchange Rate: Recurrent Neural Network
Student Loan: Neural Network
Exchange Rate Prediction
Stock Returns: Neural Network
Numerai
Exchange Rate: Recurrent Neural Network
Additional Programming Topics
Virtual Environments
Pipelines and pickles
Column Transformers
Pipelines and pickles
Column Transformers