数据、人工智能和云计算课程

• 中间的技能水平
• 4.5+
• 198

Learn to build recommendation engines in Python using machine learning techniques.

• 中间的技能水平
• 4.6+
• 188

Master RAG with Weaviate! Embed text and images for retrieval, and experiment with vector, BM25, and hybrid search.

• 中间的技能水平
• 4.8+
• 186

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

• 中间的技能水平
• 4.5+
• 179

Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.

• 中间的技能水平
• 4.7+
• 178

Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.

• 中间的技能水平
• 4.6+
• 177

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

• 中间的技能水平
• 4.4+
• 173

Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.

• 中间的技能水平
• 4.8+
• 172

Learn to import, manipulate, and transform data in Java using the Tablesaw library. Work with CSV files, tabular structures, and complex JSON formats.

• 中间的技能水平
• 4.7+
• 172

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

• 中间的技能水平
• 4.5+
• 169

Discover how to talk to your data using text-to-query AI agents with MongoDB and LangGraph.

• 中间的技能水平
• 4.2+
• 169

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

• 中间的技能水平
• 4.8+
• 165

Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.

• 中间的技能水平
• 4.4+
• 164

In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.

• 中间的技能水平
• 4.5+
• 159

Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.

• 中间的技能水平
• 4.7+
• 157

Create a healthcare AI agent using Haystack, an open-source framework for orchestrating LLMs and external components.

• 中间的技能水平
• 4.2+
• 152

In this course youll learn how to create static and interactive dashboards using flexdashboard and shiny.

• 中间的技能水平
• 4.7+
• 145

Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

• 中间的技能水平
• 4.8+
• 142

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

• 中间的技能水平
• 4.7+
• 139

Master data cleaning in Java using statistical methods, transformations, and validation for reliable apps.

• 中间的技能水平
• 4.7+
• 138

Practice Tableau with our healthcare case study. Analyze data, uncover efficiency insights, and build a dashboard.

• 中间的技能水平
• 4.6+
• 138

Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.

• 中间的技能水平
• 4.6+
• 138

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

• 中间的技能水平
• 4.5+
• 136

Learn the bag of words technique for text mining with R.

• 中间的技能水平
• 4.8+
• 135

Manipulate text data, analyze it and more by mastering regular expressions and string distances in R.

• 中间的技能水平
• 4.6+
• 134

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

• 中间的技能水平
• 4.5+
• 126

Learn to easily summarize and manipulate lists using the purrr package.

• 中间的技能水平
• 4.6+
• 122

Learn statistical tests for identifying outliers and how to use sophisticated anomaly scoring algorithms.

• 中间的技能水平
• 4.4+
• 119

In this course youll learn how to use data science for several common marketing tasks.

• 中间的技能水平
• 4.8+
• 117

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

• 中间的技能水平
• 4.6+
• 117

Learn how to access financial data from local files as well as from internet sources.