Veri, Yapay Zeka ve Bulut Kursları

• İleri SeviyeBeceri Seviyesi
• 4.4+
• 527

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

• İleri SeviyeBeceri Seviyesi
• 4.6+
• 511

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

• İleri SeviyeBeceri Seviyesi
• 4.7+
• 468

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

• İleri SeviyeBeceri Seviyesi
• 4.5+
• 445

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

• İleri SeviyeBeceri Seviyesi
• 4.4+
• 418

Learn how to make GenAI models truly reflect human values while gaining hands-on experience with advanced LLMs.

• İleri SeviyeBeceri Seviyesi
• 4.5+
• 408

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

• İleri SeviyeBeceri Seviyesi
• 4.7+
• 406

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.

• İleri SeviyeBeceri Seviyesi
• 4.4+
• 401

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

• İleri SeviyeBeceri Seviyesi
• 4.7+
• 394

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

• İleri SeviyeBeceri Seviyesi
• 4.4+
• 360

Learn to build pipelines that stand the test of time.

• İleri SeviyeBeceri Seviyesi
• 4.3+
• 335

In this course youll learn how to perform inference using linear models.

• İleri SeviyeBeceri Seviyesi
• 4.6+
• 330

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

• İleri SeviyeBeceri Seviyesi
• 4.5+
• 319

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

• İleri SeviyeBeceri Seviyesi
• 4.6+
• 315

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

• İleri SeviyeBeceri Seviyesi
• 4.6+
• 310

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

• İleri SeviyeBeceri Seviyesi
• 4.6+
• 298

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

• İleri SeviyeBeceri Seviyesi
• 4.7+
• 263

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

• İleri SeviyeBeceri Seviyesi
• 4.5+
• 260

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

• İleri SeviyeBeceri Seviyesi
• 4.3+
• 254

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

• İleri SeviyeBeceri Seviyesi
• 4.6+
• 246

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

• İleri SeviyeBeceri Seviyesi
• 4.7+
• 242

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

• İleri SeviyeBeceri Seviyesi
• 4.3+
• 238

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

• İleri SeviyeBeceri Seviyesi
• 4.6+
• 213

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

• İleri SeviyeBeceri Seviyesi
• 4.7+
• 201

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

• İleri SeviyeBeceri Seviyesi
• 4.7+
• 195

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

• İleri SeviyeBeceri Seviyesi
• 4.5+
• 194

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

• İleri SeviyeBeceri Seviyesi
• 4.5+
• 184

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

• İleri SeviyeBeceri Seviyesi
• 4.5+
• 179

Learn to use the Bioconductor package limma for differential gene expression analysis.

• İleri SeviyeBeceri Seviyesi
• 4.4+
• 174

Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.

• İleri SeviyeBeceri Seviyesi
• 4.6+
• 171

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