- Welcome from your Instructors!
- Python Packages for Data Science
Online
9 Weeks
Free
Quick facts
particular | details | |
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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Course overview
The Statistics for Data Science with Python online course introduces you to the basics of statistical procedures and methods used for data analysis. After completing this programme, you will have practical knowledge of essential topics in statistics, including – data collection, summarizing data using descriptive statistics, displaying and visualizing data, and examining relationships between variables.
The Statistics for Data Science with Python syllabus also includes hypothesis testing, probability distributions, expected values, ANOVA (analysis of variance), correlation, and regression analysis. You will also get hands-on training in statistical analysis using Jupyter notebooks and Python – the tools of choice for Data Scientists and Data Analysts.
At the end of the Statistics for Data Science with Python course, you will undertake a project to apply various concepts learned during the course and solve a Data Science problem that involves a real-life inspired scenario. Coursera also provides a certificate upon course completion, which offers tangible career benefits. However, you must pay a fee to get the certification.
The highlights
- An IBM offering
- Purchasable and shareable certificate
- Flexible deadlines
- Takes 12 hours to complete
- Delivered in English
- Course Videos & Readings
- Graded assignments
- Hands-on training
Program offerings
- Hands-on training
- Delivered in english
- Course videos
- Readings
- Graded assignments
- Flexible deadlines
- Purchasable and shareable certificate
Course and certificate fees
Type of course
There are two options available to you. You can opt for the certificate experience, for which you will have to pay a fee. However, if you only wish to learn and don’t want a certificate, you can also audit the Statistics for Data Science with Python online programme for free.
Statistics for Data Science with Python fee structure
Course | Fee in INR |
Statistics for Data Science with Python (audit only) | Free |
Statistics for Data Science with Python 1 Month | Rs. 3,177/- |
Statistics for Data Science with Python 3 Months | Rs. 6,355/- |
Statistics for Data Science with Python 6 Months | Rs. 9,532/- |
certificate availability
certificate providing authority
certificate fees
Eligibility criteria
The Statistics for Data Science with Python programme does not mandate any prerequisites for joining. However, you should complete the Python for Data Science course before applying for this programme.
Moreover, if you'd like to receive a certificate of completion, you need to complete the entire course curriculum successfully.
What you will learn
After completing the Statistics for Data Science with Python course, you will be able to:
- Conduct hypothesis tests, regression analysis, and correlation tests
- Apply and calculate measures of dispersion and measures of central tendency to grouped and ungrouped data
- Summarise, present, and visualize data in a clear and concise way which provides practical insights to non-statisticians
- Demonstrate mastery in statistical analysis using Jupyter Notebooks and Python
- Identify appropriate hypothesis tests to apply on standard data sets
Who it is for
This Statistics for Data Science with Python training course is ideal for various students and professionals who intend to apply to data and statistics-driven jobs such as Data Analysts, Business Analysts, Statisticians, Data Scientists, and Researchers.
Admission details
To participate in the Statistics for Data Science with Python course by Coursera, follow these steps:
Step -1. Gain access to Coursera's website.
Step -2. Sign in with your existing Coursera credentials or create a new account. Next, read the course details.
Step -3. On the top of the course page, you’ll find the “Enroll for free” option. Click on the option.
Step -4. A pop-up page will appear, with two options i.e., audit only and purchase the certificate. Choose according to your preference.
Step -5. You’ll be redirected to the payment gateway if you want to purchase the course. Otherwise, you can start auditing the course immediately.
Filling the form
The Statistics for Data Science with Python certification online course doesn’t have an application form. You just have to sign in using your Coursera account to access the material. Alternatively, your Google and Facebook credentials can also be used to sign in.
The syllabus
Week 1: Course Introduction and Python Basics
Videos
Readings
- Course Overview
- (Optional) Basics of Jupyter Notebooks
Week 2: Introduction & Descriptive Statistics
Videos
- Measure of Central Tendency
- Types of Data
- Welcome to Statistics!
- Measure of Dispersion
Practice Exercises
- Practice Quiz - Introduction to Descriptive Statistics
- Introduction and Descriptive Statistics
Week 3: Data Visualisation
Videos
- Statistical Charts
- Statistics by Groups
- Visualisation Fundamentals
- Introducing the teacher’s rating data
Practice Exercises
- Practice Quiz - Data Visualization
- Data Visualization
Week 4: Introduction to Probability Distributions
Videos
- Normal Distribution
- State your hypothesis
- Random Numbers & Probability Distributions
- Probability of Getting a High or Low Teaching Evaluation
- T distribution
Readings
- Alpha (α) and P-value
- Standard Normal Table
Practice Exercises
- Practice Quiz - Introduction to Probability Distribution
- Introduction to Probability Distribution
Week 5: Hypothesis testing
Videos
- ANOVA
- Dealing with tails and rejections
- z-test or t-test
- Correlation tests
- Equal vs unequal variances
Practice Exercises
- Practice Quiz - Hypothesis Testing
- Hypothesis Testing
Week 6: Regression Analysis
Videos
- Regression in place of ANOVA
- Regression in place of t-test
- Regression - the workhorse of statistical analysis
- Regression in place of Correlation
Practice Exercises
- Practice Quiz - Regression analysis
- Regression Analysis
Week 7: Project Case: Boston Housing Data
Readings
- Project Case Scenario
- Overview of Project Tasks
- Task 1: Become familiar with the dataset
- Task 2: Create or Login into IBM cloud to use Watson Studio
- Task 3: Load in the Dataset in your Jupyter Notebook
- Task 4: Generate Descriptive Statistics and Visualizations
- Task 5: Use the appropriate tests to answer the questions provided
- Task 6: Share your Jupyter Notebook
Week 8: Final Exam
Week 9: Other Resources
Reading
- IBM Digital Badge
Practice Exercise
- Opt-in to receive your badge!
Scholarship Details
If you can’t afford to pay for the Statistics for Data Science with Python certification, you can apply for the financial aid program. To apply for financial assistance, you must submit an application form.
The form requires you to provide details pertaining to your educational qualifications, career motivation, and financial constraints. You will receive an email upon application approval, which typically takes 15 days.
How it helps
The main benefit of enrolling in the Statistics for Data Science with Python program is that you can audit the course for free. Also, the program is designed by IBM and delivered by Coursera, ensuring a quality learning experience. Moreover, the course is a self-paced one, meaning you can study at your own convenience.
Lastly, if you pay the certification fee, you will get an industry-recognized certificate from Coursera, which will enable you to apply for lucrative positions with confidence.
Instructors

Ms Aije Egwaikhide
Senior Data Scientist
IBM
Other Bachelors, Other Masters
FAQs
The Statistics for Data Science with Python online course doesn’t offer any university credit upon course completion. However, some universities may accept Coursera certificates for credit. It’s best to check with the institution to learn more.
The course duration is nine weeks.
Yes, Coursera provides financial assistance to those who cannot afford the course fee.
No, you don’t need to pay anything to participate. A fee is only applicable if you wish to earn a certificate at course completion.
Yes, this programme is a part of Data Science Fundamentals with Python and SQL Specialisation.