数据、人工智能和云计算课程

• 先进的技能水平
• 4.6+
• 677

Prepare for your next coding interviews in Python.

• 基本的技能水平
• 4.6+
• 671

Create visualizations and dynamic dashboards with Databricks, turning raw data into clear and actionable insights.

• 中间的技能水平
• 4.6+
• 652

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

• 先进的技能水平
• 4.6+
• 650

Learn how to transform raw data into clean, reliable models with dbt through hands-on, real-world exercises.

• 中间的技能水平
• 4.6+
• 639

Learn to implement distributed data management and machine learning in Spark using the PySpark package.

• 中间的技能水平
• 4.4+
• 634

Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

• 中间的技能水平
• 4.5+
• 627

Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.

• 基本的技能水平
• 4.7+
• 624

Unlock Alteryx for data transformation, mastering Crosstab, Transpose, and workflow optimization in this interactive course.

• 基本的技能水平
• 4.7+
• 624

Learn how to efficiently transform, clean, and analyze data using Polars, a Python library for fast data manipulation.

• 中间的技能水平
• 4.6+
• 622

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

• 基本的技能水平
• 4.8+
• 619

Learn essential finance math skills with practical Excel exercises and real-world examples.

• 中间的技能水平
• 4.7+
• 619

This course will show you how to integrate spatial data into your Python Data Science workflow.

• 基本的技能水平
• 4.7+
• 618

Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.

• 基本的技能水平
• 4.5+
• 613

Gain a clear understanding of GDPR principles and how to set up GDPR-compliant processes in this comprehensive course.

• 中间的技能水平
• 4.6+
• 612

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

• 中间的技能水平
• 4.6+
• 609

Use Seaborns sophisticated visualization tools to make beautiful, informative visualizations with ease.

• 中间的技能水平
• 4.4+
• 609

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.

• 基本的技能水平
• 4.6+
• 608

Using Python and NumPy, learn the most fundamental financial concepts.

• 中间的技能水平
• 4.7+
• 607

Boost your coding with Windsurf, the AI-powered IDE that helps you build, debug, and deploy faster.

• 中间的技能水平
• 4.6+
• 607

Learn how to structure your PostgreSQL queries to run in a fraction of the time.

• 中间的技能水平
• 4.4+
• 605

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

• 先进的技能水平
• 4.7+
• 595

Learn how to build intelligent agents that reason, act, and solve real-world tasks using Python.

• 基本的技能水平
• 4.6+
• 593

Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!

• 基本的技能水平
• 4.4+
• 585

Stop fighting Excel and start talking to it! Use Copilot in Excel to clean data, build charts, and get answers faster.

• 中间的技能水平
• 4.6+
• 582

Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

• 中间的技能水平
• 4.5+
• 581

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

• 基本的技能水平
• 4.3+
• 577

Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

• 中间的技能水平
• 4.6+
• 576

Learn to perform linear and logistic regression with multiple explanatory variables.

• 先进的技能水平
• 4.6+
• 576

Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.

• 基本的技能水平
• 4.4+
• 570

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.