Create personalized learning paths for your organization

The secret to closing the data skills gap isn’t about hiring new talent. The solution is already on your team. With custom tracks, you can:

  • Support your data transformation programs
  • Leverage our courses, projects, and assessments
  • Close your team’s skill gaps
Screenshot of track cards

Custom track recipe cards

Follow these recommendations from our expert Learning Solutions Architects to build your data skill program. Just like when cooking, feel free to personalize these recipes based on your organization’s business and technology challenges.

SQL for Data Analysts

Use SQL to effectively analyze data and effectively answer business questions using data in databases.

  1. Introduction to SQLCourse
  2. Analyze International Debt StatisticsProject
  3. Joining Data with SQLCourse
  4. What and Where are the World's Oldest Businesses?Project
  5. Intermediate SQLCourse
  6. Data Analysis with SQL (PostgreSQL)Assessment
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From Spreadsheets to Python

You need a programming language like Python your analyses get more complex or your datasets get bigger. This track provides a gentle transition into data analysis using Python.

  1. Pivot Tables in SpreadsheetsCourse
  2. Python for Spreadsheet UsersCourse
  3. The Android App Market on Google PlayProject
  4. Pandas Joins for Spreadsheet UsersCourse
  5. The GitHub History of the Scala LanguageProject
  6. Reshaping Data with pandasCourse
  7. Data Manipulation with PythonAssessment
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Regression Fundamentals for Healthcare

This track lets you begin your journey through statistics, covering descriptive statistics and correlation, before moving on to linear and logistic regression.

  1. Introduction to Statistics in RCourse
  2. Introduction to Regression in RCourse
  3. Intermediate Regression in RCourse
  4. What Your Heart Rate Is Telling YouProject
  5. Kidney Stones and Simpson's ParadoxProject
  6. Statistics Fundamentals with RAssessment
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Inference and Experimentation in Python

Learn the sampling and hypothesis techniques to collect data and perform experiments and make data-driven improvements to your business.

  1. Foundations of Probability in PythonCourse
  2. Statistical Simulation in PythonCourse
  3. Experimental Design in PythonCourse
  4. Customer Analytics and A/B Testing in PythonCourse
  5. Mobile Games A/B Testing with Cookie CatsProject
  6. Statistics Fundamentals with PythonAssessment
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Machine Learning for Finance

From working with time-series data to creating linear models, decision trees, random forests, and neural networks—this track is designed for finance professionals who would like to use machine learning to model risk and make accurate predictions.

  1. Credit Risk Modeling in PythonCourse
  2. Machine Learning for Finance in PythonCourse
  3. Predicting Credit Card ApprovalsProject
  4. Machine Learning Fundamentals in PythonAssessment
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Marketing Analytics in Python

Level-up your marketing team’s reporting skills using Python. In this track, you’ll learn how to translate common business questions into measurable outcomes and visualizations.

  1. Analyzing Marketing Campaigns with pandasCourse
  2. Manipulating Time Series Data with PythonCourse
  3. Generating Keywords for Google AdsProject
  4. Predicting CTR with Machine Learning in PythonCourse
  5. Comparing Search Interest with Google TrendsProject
  6. Data Manipulation with PythonAssessment
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Retail Analytics in Python

Help your business and data analysts translate the vast amounts of customer transaction and viewing data into simple rules so you can deliver higher converting products promotion and recommendations.

  1. Market Basket Analysis in PythonCourse
  2. Supervised Learning with scikit-learnCourse
  3. Introduction to Natural Language Processing in PythonCourse
  4. Building Recommendation Engines in PythonCourse
  5. Book Recommendations from Charles DarwinProject
  6. Data Manipulation with PythonAssessment
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Data Visualization for Analysts in Python

Reveal hidden patterns in your data and learn how to communicate data insights to others using Matplotlib and Seaborn.

  1. Introduction to Data Visualization with MatplotlibCourse
  2. Introduction to Data Visualization with SeabornCourse
  3. A New Era of Data Analysis in BaseballProject
  4. Data Visualization in PythonAssessment
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Unsupervised Machine Learning in Python

Unsupervised machine learning lets you identify patterns and natural groupings within your data. This track takes you through important techniques such as principal component analysis, and hierarchical and k-means cluster analysis.

  1. Unsupervised Learning in PythonCourse
  2. Cluster Analysis in PythonCourse
  3. Reducing Traffic Mortality in the USAProject
  4. Dimensionality Reduction in PythonCourse
  5. Comparing Cosmetics by IngredientsProject
  6. Machine Learning Fundamentals in PythonAssessment
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Introduction to Data Engineering in Python

Expand your team's Python skills so they can support your data engineering efforts.

  1. Data Engineering for EveryoneCourse
  2. Introduction to Data EngineeringCourse
  3. Streamline Data Ingestion with pandasCourse
  4. Streamlining Employee DataProject
  5. Importing and Cleaning Data in PythonAssessment
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Understanding Data in R

In this track, you'll learn the basics of data-driven decision-making and get to apply these skills using R to real-life examples from the world of finance, marketing, and operations.

  1. Data-Driven Decision MakingCourse
  2. Introduction to the TidyverseCourse
  3. Dr. Semmelweis and the Discovery of HandwashingProject
  4. Understanding and Interpreting Data AssessmentAssessment
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Sentiment Analysis in Python

Learn how how to parse large amounts of data make sense of the sentiment expressed on various documents and social channels about your product or services.

  1. Introduction to Natural Language Processing in PythonCourse
  2. Sentiment Analysis in PythonCourse
  3. Extract Stock Sentiment from News HeadlinesProject
  4. Python ProgrammingAssessment
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Need advice creating your custom tracks ?

We understand that data fluency isn’t one-size-fits-all. That’s why our Learning Solutions Architects will partner with you to help you tailor learning to your organization. Whatever your goal, whether it’s improving data fluency or supporting a transition to open-source technologies, our team is here to help.

  • We’ll learn about your team’s learning goals.

  • We’ll help you map your learning journey to meet your targets.

  • We’ll work with you to assign and measure adoption of your tracks.

Custom track best practices

Give your track an engaging title.

We recommend including your company name in front of the title to really make it stand out. For example: DataCamp: Upgrading from Excel to SQL.

Include a clear description.

Remember to add what skill are being taught, how they will benefit you business, and who should take your custom track. This information will encourage other employees to enroll in your track.

Promote your custom tracks.

Assign your custom track, highlight it on your intranet, and celebrate employees that receive their certificate of completion.

For more recommendations and support, please contact your Customer Success Manager.

Head Headshot

We were building a learning cohort curriculum, and our Customer Success Manager at DataCamp helped map out courses that aligned to our curriculum, which was critical in building the learning cohort.

Head of Training and Talent at an International Government Agency


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