Probability and Statistics with Python
Skill Path
Gain the probability and statistics skills you need to build solid foundations for your data career. You'll learn the basic statistical analysis and probability techniques as well as the fundamentals of Python. By the end, you'll be able to gather insights, perform data analysis from start to finish and make educated assumptions for the future.
- Beginner friendly
- 4 months (5 hrs/week)
- Self paced
- 12 Courses
- 11 projects
Overview of Python courses
Python skills you'll learn
- ✓ Cleaning, preparing and analyzing data with Python
- ✓ Creating insightful data visualizations
- ✓ Using statistics to perform descriptive analytics
- ✓ Using probabilities to perform predictive analysis
Outline of Python courses
4 steps · 12 courses
Part 1: Python Introduction [4 courses]
Learn the foundations of Python and programming.
- Course 1
Introduction to Python Programming
2hDevelop foundational Python programming skills by writing code, working with variables, and processing numerical and text data.
Course Objectives ▾
- Write computer programs using Python
- Save values using variables
- Process numerical data and text data
- Create lists using Python
- Course 2
Basic Operators and Data Structures in Python
5hStrengthen Python fundamentals by using loops, conditional logic, operators, and dictionaries to manipulate data and construct frequency tables.
Course Objectives ▾
- Use for loops to repeat processes and conduct data analysis
- Implement if, else, and elif statements in programming logic
- Employ logical and comparison operators in Python
- Develop and update Python dictionaries for data manipulation
- Construct frequency tables using dictionaries for data analytics
- Course 3
Python Functions and Jupyter Notebook
7hCreate reusable Python functions and run analyses in Jupyter Notebook to organize code, debug logic, and complete portfolio-ready data projects.
Course Objectives ▾
- Write Python functions
- Debug functions
- Define function arguments
- Write functions that return multiple variables
- Employ Jupyter notebook
- Build a portfolio project
- Course 4
Intermediate Python for Data Science
8hStrengthen your Python data science skills by cleaning text data, working with dates and times, and applying object-oriented programming concepts.
Course Objectives ▾
- Clean and analyze text data
- Define object-oriented programming in Python
- Process dates and times
Part 2: Data Analysis and Visualization [2 courses]
Learn how Python and Pandas make data analysis and visualization easy.
- Course 1
Introduction to Pandas and NumPy for Data Analysis
13hDevelop practical skills with NumPy and pandas to explore, clean, and analyze data efficiently using real datasets and guided practice.
Course Objectives ▾
- Improve your workflow using vectorized operations
- Select data by value using Boolean indexing
- Analyze data using pandas and NumPy
- Course 2
Introduction to Data Visualization in Python
7hApply statistical reasoning to visualization by combining Python plotting tools with sound design choices to communicate patterns, trends, and insights clearly.
Course Objectives ▾
- Visualize time series data with line plots
- Define correlations and visualize them with scatter plots
- Visualize frequency distributions with bar plots and histograms
- Improve your exploratory data visualization workflow using pandas
- Visualize multiple variables using Seaborn's relational plots
Part 3: Data Cleaning with Python [1 courses]
Learn the basics of data cleaning in Python.
- Course 1
Data Cleaning and Analysis in Python
11hPractice cleaning and preparing messy datasets in Python by aggregating, reshaping, and combining data for efficient, real-world analysis.
Course Objectives ▾
- Employ data aggregation techniques
- Combine datasets
- Transform and reshape data
- Clean strings and resolve missing data
Part 4: Probability and Statistics with Python [5 courses]
Learn probability and statistics for more robust data analysis.
- Course 1
Introduction to Statistics in Python
8hPractice core statistical techniques in Python to sample data, analyze variables, and visualize frequency distributions for real projects.
Course Objectives ▾
- Sample data using simple random sampling, stratified sampling, and cluster sampling
- Measure variables in statistics
- Create frequency distribution tables
- Course 2
Intermediate Statistics in Python
8hDevelop practical skills to summarize distributions, measure variability, and compare values using core statistical tools in Python.
Course Objectives ▾
- Summarize 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
- Compare values using z-scores
- Course 3
Introduction to Probability in Python
4hBuild a practical foundation in probability using Python, covering random experiments, core rules, and counting techniques used in data analysis.
Course Objectives ▾
- Estimate theoretical and empirical probabilities
- Employ the fundamental rules of probability
- Employ combinations and permutations
- Course 4
Introduction to Conditional Probability in Python
5hExtend probability fundamentals to conditional reasoning, independence, and prior knowledge, culminating in a Naive Bayes spam filter.
Course Objectives ▾
- Assign probabilities based on conditions
- Assign probabilities based on event independence
- Assign probabilities based on prior knowledge
- Create spam filters using multinomial Naive Bayes
- Course 5
Hypothesis Testing in Python
3hPractice hypothesis testing in Python by running chi-square and permutation tests to evaluate real-world outcomes and statistical significance.
Course Objectives ▾
- Perform a permutation test
- Perform significance testing to understand an outcome's importance
- Define regular and multi-category chi-squared tests
Python projects you'll build
11 hands-on projects across the path
Winning Jeopardy
For this project, you'll take on the role of a Jeopardy contestant looking for any edge to win. You'll work with a dataset of 20,000 Jeopardy questions using Python and pandas to analyze question and answer text and uncover helpful patterns.
Investigative Statistical Analysis - Analyzing Accuracy in Data Presentation
For this project, we'll step into the role of data journalists to analyze movie ratings data and determine if there's evidence of bias in Fandango's rating system. We'll apply statistical analysis skills using Python.
Exploring eBay Car Sales Data
For this project, we'll assume the role of data analysts for a used car classifieds service to explore and clean a dataset of car listings from eBay Kleinanzeigen, a section of the German eBay website.
Finding the Best Markets to Advertise In
For this project, we'll assume the role of analysts for an e-learning company that wants to promote its programming courses. Using Python and pandas, we'll explore survey data from new coders to determine the two best markets to advertise in based on the number of potential customers and their willingness to pay.
Clean and Analyze Employee Exit Surveys
For this project, we'll assume the role of data analysts for the Department of Education, Training and Employment and the Technical and Further Education institute in Queensland, Australia to analyze employee exit surveys and uncover insights about why employees resign.
+ 6 more projects throughout the path
Earn your Probability and Statistics with Python Certificate
Add this Python certificate to your resume or LinkedIn to showcase your skills and stand out in job applications.
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