The Best Courses to Learn pandas, NumPy and scikit-learn for Excel Users in 2026

4. Python in Excel 2025 Masterclass for Data Science - Udemy

Alexander Hagmann's Python in Excel 2025 Masterclass for Data Science on Udemy is a pick for analysts who want Python without leaving the workbook.

• Level: Requires basic Excel and Python coding skills
• Time: 7h 34m total length
• Cost: $19.99
• Best for: Running pandas and scikit-learn inside Excel cells

The course uses Microsoft's Python in Excel feature to write pandas, seaborn, and scikit-learn code directly in cells, across projects on movie revenues, Dow Jones stock prices, and Olympic medal tables. Its Udemy page lists a 4.2 out of 5 rating from 261 ratings, and Udemy listed it at $19.99 in the US when we checked on November 12, 2026.

The catch is in the requirements: a Windows desktop with a Microsoft 365 subscription (no Mac or Linux), plus basic Python skills before you start. Excel users starting from zero should take Introduction to Python first.

Our pick: Start with DataCamp's Introduction to Python, the first course of the Associate Data Scientist in Python track. Add Pandas Joins for Spreadsheet Users if lookups are most of your job.

Best pandas, NumPy and scikit-learn Courses

The best way to learn pandas, NumPy, and scikit-learn is in the order you will use them: pandas to clean and reshape data, NumPy for the arrays underneath, then scikit-learn to model. One track covers most of it, and 3 single courses cover each library on its own.

1. Associate Data Scientist in Python - DataCamp

DataCamp's Associate Data Scientist in Python track is the best single path from your first DataFrame to your first machine learning models.

• Level: 23 courses
• Time: 90 hrs
• Cost: Included with Premium
• Best for: Learning pandas and scikit-learn as one plan

The track strings together Data Manipulation with pandas, Joining Data with pandas, statistics, Matplotlib and seaborn, then Supervised Learning with scikit-learn and Unsupervised Learning in Python. It also prepares you for the Associate level of DataCamp's Data Scientist Certification.

2. Data Manipulation with pandas - DataCamp

DataCamp's Data Manipulation with pandas is the best single pandas course for analysts who already know a little Python.

• Level: Beginner
• Time: 4 hrs
• Cost: First lesson free, then included with Premium
• Best for: The pandas skills that replace filters, sorts, and pivot tables

You import and clean data, calculate summary statistics, and draw quick charts, which covers most of what an analyst does in Excel each week. Data Manipulation with pandas can also be taken with DataCamp's AI tutor, which builds unique lessons based on every learner's role, skill level, and goals.

3. Introduction to NumPy - DataCamp

DataCamp's Introduction to NumPy is the best course for understanding the arrays that pandas and scikit-learn run on.

• Level: Beginner
• Time: 4 hrs
• Cost: First lesson free, then included with Premium
• Best for: Arrays and vectorized calculations

You create, sort, filter, and update arrays using the New York City tree census, which feels close to working with a large worksheet column by column. Most Excel analysts take it after their first pandas course, once arrays start showing up in their pandas code.

4. Supervised Learning with scikit-learn - DataCamp

DataCamp's Supervised Learning with scikit-learn is the best first scikit-learn course for analysts who want predictions, not just reports.

• Level: Intermediate
• Time: 4 hrs
• Cost: First lesson free, then included with Premium
• Best for: Your first classification and regression models

It works on real-world datasets and is taught by George Boorman, a senior data analyst at Wayflyer, so the examples lean toward business questions rather than research problems. Take it once pandas feels routine.

For grouping customers or products without a target column, Unsupervised Learning in Python covers clustering and dimension reduction with scikit-learn and SciPy.

Our pick: Take DataCamp's Associate Data Scientist in Python if you want one plan to follow. If you prefer to pick and choose, Data Manipulation with pandas, then Supervised Learning with scikit-learn is the shortest route to a working model.

Best Python Data Science Courses With Certification

The best Python data science course with certification depends on whether you want DataCamp's role-based exams or a provider-branded certificate. DataCamp's tracks prepare for timed and practical exams, while IBM and Google issue professional certificates through Coursera.

1. Data Analyst in Python - DataCamp

DataCamp's Data Analyst in Python track is the best certification path for Excel analysts who want to stay analysts, just with Python.

• Level: 9 courses
• Time: 36 hrs
• Cost: Included with Premium
• Best for: Analysts who want a Python credential

The track prepares you for DataCamp's Data Analyst Certification: timed exams DA101 (2 hours) and DA201 (1 hour) plus the practical exam DA601P, completed within 30 days. The certification is included with Premium and stays valid for 2 years.

For a smaller first credential, Python Data Fundamentals prepares you for the Python Data Associate certification, a timed exam (PY101) and a practical exam (PY501P).

2. Data Scientist in Python - DataCamp

DataCamp's Data Scientist in Python track is the best certification path once pandas and scikit-learn are no longer new to you.

• Level: 9 courses
• Time: 26 hrs
• Cost: Included with Premium
• Best for: Analysts aiming at data scientist roles

It prepares you for the Data Scientist level of DataCamp's Data Scientist Certification (DS101, DS201 and the practical DS601P) and adds what analyst jobs rarely ask for: SQL, Git, Python packages and preprocessing for machine learning. Take the Associate Data Scientist in Python track first if you are still new to the libraries.

3. IBM Data Science Professional Certificate - IBM

IBM's Data Science Professional Certificate on Coursera is a well-known beginner credential that covers all 3 libraries.

• Level: Beginner level, no prior experience required
• Time: 4 months at 10 hours a week
• Cost: Included with Coursera Plus
• Best for: A brand-name certificate from a 12-course series

Its Coursera page lists pandas, NumPy, Matplotlib, seaborn, scikit-learn and SciPy among the libraries in its 12 courses, with no prior experience required. It is a bigger commitment than a single track, and the page lists 4 months at 10 hours a week.

4. Google Advanced Data Analytics Professional Certificate - Google

Google's Advanced Data Analytics Professional Certificate on Coursera can be a good credential for analysts if they already hold Google's entry-level certificate.

• Level: Advanced level, recommended experience
• Time: 6 months at 10 hours a week
• Cost: Included with Coursera Plus
• Best for: Analysts moving into regression and machine learning

Its Coursera page describes it as designed for graduates of the Google Data Analytics Certificate, covering statistical analysis, Python, regression models and machine learning across 7 courses. Excel users without that background will find the start steep, and courses are less interactive than on DataCamp.

Our pick: DataCamp's Data Analyst in Python is the most direct credential for an Excel analyst moving to Python. Choose IBM's Data Science Professional Certificate if a brand-name certificate matters more to you than exam-based proof of skills.

Best Free pandas, NumPy and scikit-learn Courses

The best free pandas course is Kaggle Learn's Pandas course, and Kaggle's Intro to Machine Learning is the best free next step. DataCamp's introductory Python courses open with a free first lesson, which is enough to see whether the format suits you.

1. Pandas - Kaggle Learn

Kaggle Learn's Pandas course is the best free way to practice pandas in the browser.

• Level: Assumes basic Python knowledge
• Time: 4 hours
• Cost: No cost, like all Kaggle Learn Courses
• Best for: Free pandas practice with a certificate

Its 6 lessons pair a short tutorial with an exercise notebook, from reading and writing data to grouping, sorting and combining tables. It assumes Kaggle's own Python course first, and it does not translate Excel habits for you.

2. Intro to Machine Learning - Kaggle Learn

Kaggle Learn's Intro to Machine Learning is the best free first look at building and validating a model.

• Level: Intermediate
• Time: 3 hours
• Cost: No cost, like all Kaggle Learn Courses
• Best for: A free first model after pandas

Its 7 lessons run from how models work through model validation, underfitting and overfitting to random forests. It is short, so expect a first model rather than a full grounding in scikit-learn.

3. Introduction to Python and Python for Spreadsheet Users, lesson 1 - DataCamp

The first lessons of DataCamp's Introduction to Python and Python for Spreadsheet Users are free, with no subscription needed.

• Level: Beginner
• Time: About 1 hour per free lesson
• Cost: Free
• Best for: Testing whether interactive learning suits you

A free first lesson is not the whole course, but it is enough to write your first lines of Python and see whether the interactive format suits you. DataCamp's free tutorials fill in the rest, from the Python in Excel tutorial to the pandas guide linked above.

Our pick: Kaggle Learn's free Pandas course is the best free option, followed by its Intro to Machine Learning course. Use the free first lessons of Introduction to Python and Python for Spreadsheet Users to try a course built around spreadsheet habits.

How We Chose These Python Data Science Courses

We built this list for analysts moving from Excel to Python, not for programmers adding a library.

• We verified every rating, review count, and learner number live on the date displayed above.
• We show no score for any course with fewer than 200 reviews; those are marked "New".
• Track ratings are computed as a review-weighted average across the courses in the track, not the track page's own rating.
• We prioritized courses whose content was updated in the last 18 months.
• We ranked entries by relevance to each goal first, then by freshness, not by rating or popularity.
• We included courses from other providers wherever they are the better choice, and said so.
• We favored courses that start from spreadsheet tasks (pivot tables, lookups, Excel files) over general programming courses.

Final Thoughts

If you are coming from Excel with no code behind you, start with DataCamp's Introduction to Python and continue through the Associate Data Scientist in Python track. The track starts with that course, so together they cover the whole question: Python basics, then pandas and scikit-learn models in one plan, with Introduction to NumPy alongside. If the spreadsheet comparisons help you learn, take Python for Spreadsheet Users before or next to it.

Analysts who need a credential should take Data Analyst in Python, and anyone on a zero budget should start with Kaggle Learn's free Pandas course. Wherever you start, pick one real workbook from your job and rebuild it in pandas as you go. It teaches more than any course on its own.