Курсы по данным, искусственному интеллекту и облачным технологиям

• ПередовойУровень мастерства
• 4.6+
• 506

Create more accurate and reliable RAG systems with Graph RAG and hybrid RAG.

• ПередовойУровень мастерства
• 4.6+
• 478

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

• ПередовойУровень мастерства
• 4.3+
• 473

Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.

• ПередовойУровень мастерства
• 4.3+
• 434

Master Databricks with Python: learn to authenticate, manage clusters, automate jobs, and query AI models programmatically.

• ПередовойУровень мастерства
• 4.7+
• 432

Learn how to approach and win competitions on Kaggle.

• ПередовойУровень мастерства
• 4.6+
• 428

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

• ПередовойУровень мастерства
• 4.7+
• 426

Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

• ПередовойУровень мастерства
• 4.6+
• 416

Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

• ПередовойУровень мастерства
• 4.3+
• 404

Learn to build pipelines that stand the test of time.

• ПередовойУровень мастерства
• 4.6+
• 401

Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.

• ПередовойУровень мастерства
• 4.7+
• 395

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

• ПередовойУровень мастерства
• 4.6+
• 364

Learn how to work with streaming data using serverless technologies on AWS.

• ПередовойУровень мастерства
• 4.4+
• 355

In this course you will learn to fit hierarchical models with random effects.

• ПередовойУровень мастерства
• 4.6+
• 346

This course covers everything you need to know to build a basic machine learning monitoring system in Python

• ПередовойУровень мастерства
• 4.5+
• 317

Build real-world applications with Python—practice using OOP and software engineering principles to write clean and maintainable code.

• ПередовойУровень мастерства
• 4.7+
• 312

Connect Java to PostgreSQL with JDBC. Write secure queries, manage transactions, and handle large datasets efficiently.

• ПередовойУровень мастерства
• 4.4+
• 299

Build AI agentic workflows that can plan, search, remember, and collaborate, using LlamaIndex.

• ПередовойУровень мастерства
• 4.7+
• 295

Learn how to write recursive queries and query hierarchical data structures.

• ПередовойУровень мастерства
• 4.2+
• 294

Learn to analyze Airbnb data using SQL in Databricks, create dashboards, and derive actionable insights.

• ПередовойУровень мастерства
• 4.6+
• 286

Sharpen your knowledge and prepare for your next interview by practicing Python machine learning interview questions.

• ПередовойУровень мастерства
• 4.8+
• 273

Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.

• ПередовойУровень мастерства
• 4.7+
• 273

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

• ПередовойУровень мастерства
• 4.6+
• 256

Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

• ПередовойУровень мастерства
• 4.7+
• 232

Develop a better intuition for advanced probability, risk assessment, and simulation techniques to make data-driven business decisions with confidence.

• ПередовойУровень мастерства
• 4.7+
• 208

Use survival analysis to work with time-to-event data and predict survival time.

• ПередовойУровень мастерства
• 4.6+
• 202

Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.

• ПередовойУровень мастерства
• 4.5+
• 201

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

• ПередовойУровень мастерства
• 4.5+
• 200

Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.

• ПередовойУровень мастерства
• 4.7+
• 193

Learn how to load, transform, and transcribe speech from raw audio files in Python.

• ПередовойУровень мастерства
• 4.7+
• 191

Learn how to write effective tests in Java using JUnit and Mockito to build robust, reliable applications with confidence.