Data Analysis with Python: Zero to Pandas
"Data Analysis with Python: Zero to Pandas" is a practical and beginner-friendly introduction to data analysis covering the basics of Python, Numpy, Pandas, Data Visualization, and Exploratory Data Analysis.
- Watch hands-on coding-focused video tutorials
- Practice coding with cloud Jupyter notebooks
- Build an end-to-end real-world course project
- Earn a verified certificate of accomplishment
There are no prerequisites for this course.
Lesson 1 - Introduction to Programming with PythonPreview
- First steps with Python & Jupyter notebooks
- Arithmetic, conditional & logical operators in Python
- Quick tour with Variables and common data types
Lesson 2 - Next Steps with PythonPreview
- Branching with if, elif, and else
- Iteration with while and for loops
- Write reusable code with Functions
- Scope of variables and exceptions
Assignment 1 - Python Basics PracticePreview
- Solve word problems using variables & arithmetic operations
- Manipulate data types using methods & operators
- Use branching and iterations to translate ideas into code
- Explore the documentation and get help from the community
Lesson 3 - Numerical Computing with Numpy
- Going from Python lists to Numpy arrays
- Working with multi-dimensional arrays
- Array operations, slicing and broadcasting
- Working with CSV data files
Assignment 2 - Numpy Array Operations
- Explore the Numpy documentation website
- Demonstrate usage 5 numpy array operations
- Publish a Jupyter notebook with explanations
- Share your work with the course community
Lesson 4 - Analyzing Tabular Data with Pandas
- Reading and writing CSV data with Pandas
- Querying, filtering and sorting data frames
- Grouping and aggregation for data summarization
- Merging and joining data from multiple sources
Assignment 3 - Pandas Practice
- Create data frames from CSV files
- Query and index operations on data frames
- Group, merge and aggregate data frames
- Fix missing and invalid values in data
Lesson 5 - Visualization with Matplotlib and Seaborn
- Basic visualizations with Matplotlib
- Advanced visualizations with Seaborn
- Tips for customizing and styling charts
- Plotting images and grids of charts
Course Project - Exploratory Data Analysis
- Find a real-world dataset of your choice online
- Use Numpy & Pandas to parse, clean & analyze data
- Use Matplotlib & Seaborn to create visualizations
- Ask and answer interesting questions about the data
Lesson 6 - Exploratory Data Analysis - A Case Study
- Finding a good real-world dataset for EDA
- Data loading, cleaning and preprocessing
- Exploratory analysis and visualization
- Answering questions and making inferences
Certificate of Accomplishment
Earn a verified certificate of accomplishment (sample by completing all weekly assignments and the course project. The certificate can be added to your LinkedIn profile, linked from your Resume, and downloaded as a PDF.
Instructor - Aakash N S
Aakash N S is the co-founder and CEO of Jovian. Previously, Aakash has worked as a software engineer (APIs & Data Platforms) at Twitter in Ireland & San Francisco and graduated from the Indian Institute of Technology, Bombay. He’s also an avid blogger, open-source contributor, and online educator.
If you have general questions about the course, please browse through this list first. Click/tap on a question to expand it and view the answer. If there’s something that’s not answered here, please reply to this topic with your question. For lecture & assignment related queries, please ask question on the respective threads.
What will I learn in this course? Why is it titled "Zero to Pandas"?
Data Analysis with Python: Zero to Pandas is an online course intended to provide a coding-first introduction to data analysis.
The course takes a hands-on coding-focused approach and will be taught using live interactive Jupyter notebooks, allowing students to follow along and experiment. Theoretical concepts will be explained in simple terms using code. Participants will receive weekly assignments and work on a project with a real-world dataset to test their skills. Upon successful completion of the course, participants will receive a certificate of completion.
The following topics are covered:
- Python & Jupyter Fundamentals
- Numpy for data processing
- Pandas for working with tabular data
- Visualization with Matplotlib and Seaborn
- Exploratory Data Analysis: A Case Study
The course is called “Zero to Pandas” because it assumes no prior knowledge of Python (i.e. you can start from Zero), and by the end of the five weeks, you’ll be familiar with running data analysis with Python.
Access the Course Syllabus for more details.
What is the duration of this course?
This course runs for 6 weeks. You can enroll, watch the session recordings and submit the assignments and course project during this period. The submissions will be evaluated by us and you shall be provided with the certificate on successful completion of all assignments and project.
Who is eligible for taking this course? Are there any prerequisites?
This is a beginner-friendly course, and no prior knowledge of Data Science or Python is assumed. You DON’T require a college degree (B.Tech, Masters, PhD etc.) to participate in this course.
You do need to have a computer (laptop/desktop) with a good internet connection to watch the video lectures, run the code online, and participate in the forum discussions.
What do I need to do get a certificate for this course?
To become eligible for a “Certificate of Completion”, you need to satisfy the all of following criteria:
- Make valid submissions for all 3 weekly assignments in the course (the course team will evaluate & accept/reject submission)
- Make a valid submission towards the course project
- Do not violate the Code of Conduct
More details regarding the assignments and the course project will be shared during the course. Please note that we reserve the right to withhold/cancel any participant’s certificate if we are not satisfied with the quality of their submissions or find them in violation of the Code of Conduct and Academic Honesty Policy.
Who is issuing the certificate? Is it by some educational institution?
The Certificate of Completion will be issued by Jovian . Please note that Jovian is not a registered educational institution, and this certificate will not count towards your higher education/college credits. The certificate simply indicates that you have completed all the required coursework for this course. Moreover, Jovian reserves the right to withhold/cancel any participant’s certificate if we are not satisfied with the quality of their submissions or find them in violation of the Code of Conduct.
Where can I watch the lectures?
Video lectures are available on the course page. Go to zerotopandas.com and open the particular lesson. You will find the video inside the lesson page.
Do I need to set up anything on my computer to participate in this course?
No, you do not need to install any additional software on your computer to participate in this course. You just need a computer (laptop/desktop) with a working internet connection and a modern web browser (like Google Chrome or Firefox) to watch the lectures, participate in forum discussions, and complete the assignments.
You will be able to do all the assignments using free online computing platforms that you can access from your web browser. More details about these will be shared during the video lectures and on the individual assignment threads.
Do I need a Graphical Processing Unit (GPU) for this course?
No, for this course you do not require any Graphical Processing Unit(GPU). If in case you require a GPU, you don't have to buy it. Online Platforms like Google Colab provides free access to GPUs for a limited amount of time every week. The free tier should be sufficient to fulfill all your requirements.
How will the course material (Jupyter notebooks, assignments be shared)?
The lectures will be taught using Jupyter notebooks, an browser-based interactive programming environment. The lecture notebooks and assignements will be shared using Jovian, a platform for sharing Jupyter notebooks and data science projects. You will be able to run the shared Jupyter notebooks directly from Jovian.
How much time am I expected to put in every week for this course?
The coursework should not take up more than 8-10 hours per week. If you’re able to do it in lesser time, that’s great.
In general, even if you’re a full-time student or working professional, you should be able to follow along and complete the coursework comfortably, if you remain motivated.
Can I watch the video lectures without registering or doing assignments?
Sure, you can audit the course by just viewing the video lectures, but we highly recommend that you try out the assignments and put in the work required to earn a certificate. Doing the assignments will help you apply the concepts and get hands-on experience with data analysis. Interactive Juptyer notebooks are a great way to learn & experiment with the code, and we’ve put in a lot of effort to prepare these resources for you. We hope you will find it worthwhile to do the assignments & exercises.
Is there any textbook for reference during the course?
No, there is no textbook for this course. This course is taught entirely using Jupyter notebook, which include a fair bit of explanation along with code, graphs, links to references etc. We will provide links to reading material, blog posts & other free resources online.
Who is the instructor for this course?
The instructor for this course is
Aakash N S
Aakash is the co-founder and CEO of Jovian, a platform to learn Data Science & Machine Learning.
Jovian is also a project management and collaboration platform for Jupyter notebooks.
Prior to starting Jovian, Aakash worked asa software engineer (APIs & Data Platforms)
at Twitter in Ireland & San Francisco and graduated from IIT Bombay.
He’s also a Competitions Expert on Kaggle, an avid blogger, open source contributor
and online educator.
How will the assignments be graded? Is there a minimum passing grade?
- Assignments will require completing tasks such as creating a Jovian notebook, writing a blog post etc.
- Assignment submission can be done on assignment page using the Jovian notebook link
- Some assignments are automated, which means they will be evaluated automatically. Few assignments will be evaluated by the course team.
- You will be graded as "PASS" or "FAIL" according to the assignment evaluation. If you get "FAIL" grade, you will get chance to work on the assignment again and resubmit it.
More details about the submission will be provided in the individual topics for each assignment.
Where can I ask questions, if I have doubts or need clarifications?
Depending on the type of question, please choose one of the following:
If you have questions on any topic covered in a lecture/assignment, you can post them in the respective lessons' discusison page. Someone from the course team or the community will try to answer your question. Before asking, please scroll through the thread to check if your question has already been asked/answered.
If you have questions about the course itself, you can post your question on the discussion page of the course
- You can also ask your question in the zerotopandas channel of Jovian community slack group.
If you do not want to ask a question publicly or need more assistance, you can send an email to email@example.com, and someone from the course team will respond to you over email.
We recommend asking question on the discussion pages, since in many cases other
members of the community will be able to answer questions faster than us,
and your question will also be useful for others.
Remember, no question to too simple to be asked.
Can I invite my friends or colleagues to participate in the course with me?
Yes, please spread the word and invite your friends to join in.
I'm facing harassment/abuse from another participant in the course. What should I do?
We expect all participants to follow the Code of Conduct, and we take harassment and abuse very seriously. Please reach out to us at firstname.lastname@example.org if you are a victim of harassment/abuse by another user, and we’ll investigate the matter and take strict action immediately. Once verified, we will remove the participant from the course, and for more serious matters, report it to relevant authorities.