Căi de învățare pentru dezvoltarea carierei

Learn data science in Python, from data manipulation to machine learning. This track provides the skills needed to succeed as a data scientist!

Gain the SQL skills you need to query a database, analyze the results, and become a SQL proficient Data Analyst. No prior coding experience required!

Co-created with Microsoft—gain the Power BI skills you need to prepare, model, and visualize data for the PL-300 Data Analyst certification.

Learn how to integrate AI into software applications using APIs and open-source libraries. Start your journey to becoming an AI Engineer today!

Develop your data analytics skills in Python. Gain the data analyst skills to manipulate, analyze, and visualize data. No coding experience required!

Learn the fundamentals of data engineering: database design and data warehousing, working with technologies including PostgreSQL and Snowflake!

Gain in-demand skills to efficiently ingest, clean, manage data, and schedule and monitor pipelines, setting you apart in the data engineering field.

Learn Python for software development, from writing functions to defining classes. Get the necessary skills to kickstart your developer career!

Train and fine-tune the latest AI models for production, including LLMs like Llama 3. Start your journey to becoming an AI Engineer today!

Discover machine learning with Python and work towards becoming a machine learning scientist. Explore supervised, unsupervised, and deep learning.

Learn how to use R for data science, from data manipulation to machine learning. Gain the career-building skills you need to succeed in data science!

This career track teaches you everything you need to know about machine learning engineering and MLOps.

From exploratory data analysis with dplyr to data visualization with ggplot2—gain the career-building R skills you need to succeed as a data analyst!

Learn data science in Python, from data manipulation to machine learning, and gain the skills needed for the Data Scientist in Python certification!

From testing code and implementing version control to web scraping and developing packages, take the next step in your Python developer journey!

Master Tableau for data analysis and develop your skills in one of the world’s most popular BI tools. No prior experience is required.

Master Databricks, SQL, data visualization, and management in the Lakehouse Platform for the Databricks Data Analyst Associate certification.

Dive deep into advanced skills and state-of-the-art tools revolutionizing data engineering roles today with our Professional Data Engineer track.

Learn to design, query, and build in Snowflake - mastering Snowflake SQL for transformation and modeling to become a job-ready Data Engineer.

Master Java development from fundamentals to testing and optimization. Build applications that are reliable and ready to ship.

Prepare for AZ-204 by building and integrating cloud applications on Microsoft Azure with hands-on, developer-focused courses.

A statistician collects and analyzes data and helps companies make sense of quantitative data, including spotting trends and making predictions.

Gain the SQL Server skills you need to write, troubleshoot, and optimize your queries using SQL Server.

This certification learning path provides the practical skills required for the Google Cloud Engineer.

Develop essential Java skills for data engineering, from file processing and database integration to performance optimization.

Gain the career-building skills you need to succeed as an R Developer by learning to write and package code efficiently. No coding experience needed!

Learn data engineering on Databricks with SQL, Python, and Spark, and prepare for the Databricks Certified Data Engineer Associate certification.

Ensure portfolios are risk balanced, help find new trading opportunities, and evaluate asset prices using mathematical models.

Learn data science with R, from data manipulation to machine learning, and gain the skills needed for the Data Scientist in R certification!

A machine learning scientist researches new approaches and builds machine learning models.