Probability and statistics are critical in data science. They allow us to gather insights from data and determine whether what we’re seeing is meaningful. Using statistics, we can make educated assumptions and forecasts based on real-world data.

This skill path is ideal for those who’d like to develop a skill that they can use on the job, for future career growth, or for fun!

Learn probability and statistics for data science all at your own pace and from the comfort of your browser.

  • Discover how to summarize a distribution’s measures of central tendency and variability
  • Learn the fundamentals of probability and how to use them for analysis
  • Make forecasts based on previous trends or patterns in the data

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What You’ll Learn

Transform your resume by adding career skills such as probability and statistics. Our Probability and Statistics with Python Skill Path is the perfect course series for developing your skills in collecting and preparing data. This path introduces the basics of statistical analysis using Python, including sampling, working with variables, and understanding frequency distribution tables.

Here are some of the skills you can expect to master in this path:

  • Fundamentals of Python programming and data science
  • Working with text, date, and time data using Python
  • Exploring object-oriented programming
  • Working with data using vectorized operations
  • Building knowledge of Boolean indexing, pandas, and NumPy
  • Learning the basics of data visualization
  • Understanding statistics fundamentals
  • Cleaning, transforming, and combining data
  • Mastering averages, variability, and probability
  • Performing permutation and hypothesis testing
  • Using Jupyter Notebook
Data Scientist in Python Salary Increase

Data Scientists with Python skills earn $97K on average according to Payscale.com

Data Scientist in Python Job Openings

There are estimated to be more than 11 million new data science jobs by 2026

Data Scientist In Python Job Growth

Python is the #1 programming language used by data scientists.

How Our Probability and Statistics with Python Skill Path Works

Without probability and statistics, there wouldn’t be data science. They are the foundation that holds everything together. We need statistical methods to analyze and collect large data sets, and we need probability to make estimates and predictions about that data. In business, probability and statistics are pivotal for success. As a result of the importance and growing demand of probability and statistics, we’ve created a series of courses to help you master these consequential skills.

We approach teaching with hands-on, interactive learning to keep you engaged throughout our courses. No more boring videos or endless reading. You’ll hone the skills you learn with relevant practice problems while demonstrating the practical uses of these new skills with projects.

Our partnership approach sets us apart as well. Leverage our in-depth support tools and thriving community for help throughout your studies.

Here’s a quick glance at this skill path:

  • This skill path consists of the courses listed below, which cover the main components of probability and statistics that you can apply professionally right away.
  • You’ll perform hands-on data statistics and answer practice problems to validate and apply your new skills.
  • At the end of each course, you’ll complete a guided project to enhance your resume and further reinforce your new knowledge.
  • When you complete the course, you’ll receive a certificate as proof of your hard work that you can share with your professional network.
  •  After you receive your certificate, you’ll understand the fundamental framework of probabilities and statistics with Python. More advanced data science courses are available if you want to continue learning!
  • Engage with the community, get feedback on your project, and keep building.

Learn how to understand the past and predict the future. Enroll in this career path  now!

Probability and Statistics with Python Skill Path Course List

Python for Data Science: Fundamentals Part I
Learn the fundamentals of Python programming and data science.

Python for Data Science: Fundamentals Part II
Learn how to use Jupyter Notebook and how to build a portfolio project.

Python for Data Science: Intermediate
Learn important Python data science skills, how to analyze text data, how to work with dates and times, and object-oriented programming.

Pandas & NumPy Fundamentals
Learn how vectorized operations make working with data faster, selecting data by value using Boolean indexing, and using pandas and NumPy to analyze data.

Data Visualization Fundamentals
Learn how to visualize time series data with line plots, visualizing frequency distributions with bar plots and histograms, and how to speed up your exploratory data visualization workflow using Pandas.

Data Cleaning and Analysis
Learn data cleaning and analysis with pandas, how to combine datasets, how to transform and reshape data, and how to clean strings and handle missing data.

Statistics Fundamentals
Learn sampling data using simple random sampling, stratified sampling, and cluster sampling. You’ll explore variables in statistics; how they're measured; and building, visualizing, and comparing frequency distribution tables.

Statistics Intermediate: Averages and Variability
Learn summarizing a distribution using the mean, the weighted mean, the median, or the mode. Measure the variability of a distribution using the variance and the standard deviation. Learn how to locate and compare values using z-scores.

Conditional Probability
Learn to assign probabilities based on conditions, assign probabilities based on event independence, assign probabilities based on prior knowledge, and create spam filters using multinomial Naive Bayes.

Hypothesis Testing: Fundamentals
Learn how to perform a permutation test, perform significance testing to better understand an outcome's importance, and about regular and multi-category chi-square tests.

Probability: Fundamentals
Learn to estimate theoretical and empirical probabilities, use the fundamental rules of probability, and work with combinations and permutations.

Who Is This Probability and Statistics with Python Skill Path For?

Probabilities and statistics are important everywhere you go. Coupling these skills with your background in Python will take your skill set to the next level.

Whether you’re in an analyst role and need to quickly work through large sets of data, or you’re a user experience specialist who needs to process user insights and wants a much-needed promotion, this skill path will set you up for success. Start learning today for free.