Frequently Asked Questions (FAQ) | Zero to GBMs

If you have 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.

What will I learn in this course?

Machine Learning with Python: Zero to GBMs” is a practical and beginner-friendly introduction to supervised machine learning, decision trees, and gradient boosting using Python and its ecosystem of ML libraries: scikit-learn, XGBoost, and LightGBM.

Theoretical concepts will be explained in simple terms using code. Students will receive weekly assignments and work on a project to test their skills. Upon successful completion of the course, students will receive a certificate of completion.

Lesson Title Course Page Forum
Lesson 1 Linear Regression with Scikit Learn Course Page Forum Page
Lesson 2 Logistic Regression for Classification Course Page Forum Page
Lesson 3 Decision Trees and Random Forests Course Page Forum Page
Lesson 4 Gradient Boosting with LightGBM Course Page Forum Page
Lesson 5 End to End Machine Learning Project Course Page Forum Page
Lesson 6 Other Machine Learning Techniques Course Page Forum Page

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What is the duration of the course?

The course is currently in SELF PACED MODE, feel free to enroll and complete it at your own pace, we will generate your certificate once you receive a PASS grade in all the assignments and the course project.

Who is eligible for taking this course? Are there any prerequisites?

This is a beginner-friendly course, and no prior knowledge of data structures and python is assumed. You DON’T require a college degree (B.Tech, Masters, Ph.D., 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 forum discussions.

What do I need to do to get a certificate for this course?

To become eligible for a “Certificate of Completion”, you need to satisfy all of the 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

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.

Is the certificate free of cost, or do I need to pay for it?

The Certificate of Completion is FREE of COST

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. Please note that 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 Jovian YouTube channel
You can also access them from the respective lecture pages here
:point_right: Machine Learning with Python: Zero to GBMs | Jovian

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.

How will the course material (Jupyter notebooks, assignments be shared)?

The lectures will be taught using Jupyter notebooks, a browser-based interactive programming environment. The lecture notebooks and assignments 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.

There will be a separate forum topic for each assignment, where the problem statement & submission instructions will be shared. Please check the individual topics for more details regarding assignments.

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. If it’s taking you longer, then you probably need to spend some more time learning fundamentals (math, programming) alongside, and that’s going to be generally helpful for you.

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 building deep learning models. 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.

Since we are using YouTube to premiere the lectures, lecture recordings will be available for public viewing immediately after the lecture at the same link as the Livestream.

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 includes 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 project management and collaboration
platform for machine learning. Prior to starting Jovian, Aakash worked as a 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 Jupyter notebook, writing a blog post, etc.
  • The course team will evaluate submissions and either “accept” or “reject” them. If your submission is rejected, you’ll have a chance to resubmit.
  • There is no passing grade as such, we simply require that your submissions to all of the assignments are accepted.

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:

  1. If you have questions on any topic covered in a lecture/assignment, you can post them in the respective lecture/assignment threads. 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.

  2. Use the Help thread for other questions, doubts, and coding errors/issues that are not specific to a particular lecture or assignment.

  3. If you have questions about the course itself, please check the Frequently Asked Questions (this thread). If your question is not answered here, you can post a reply on this thread to ask your question.

  4. Join the Jovian Discord Server to interact with the course team, share resources and attend the study hours - Jovian Discord Server

  5. If you do not want to ask a question publicly or need more assistance, you can send an email to support@jovian.ai, and someone from the course team will respond to you over email.

We recommend asking a question on the forum, since in many cases other members of the community will be able to answer questions faster than us (we’re a small team), 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. You can also start a study group with your friends to learn together.

Is there an official study group or review session for this course?

There is no official study group or review session, but there are several unofficial study groups across various timezones that you can join to learn together with other participants. Consider starting a new study group if you don’t find one matching your timezone/city.

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 support@jovian.ai 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.

What is Jovian? What is Jovian's role in this course?

Jovian is a platform for sharing data science projects & Juptyer notebooks, used by thousands of data scientists & machine learning practitioners worldwide.

The material in this course has been prepared by the Jovian team, and the instructor, Aakash N S, is the co-founder & CEO of Jovian. All course Jupyter notebooks & assignments are shared via the Jovian platform, and the Jovian forum is used for discussions & course communications.

If your question is not answered here, you can post a reply on this thread and we shall answer it.

Hey there,

I wanted to ask if it’s possible to finish the course later or work through it at a lower pace and still get a certificate upon completion? I’m currently not able to make the time - I was very much looking forward to the course, but June/July is a bad time workwise :confused:

Thanks so much in advance for considering my request and best regards,
Jonas

3 Likes

Hey @roeder, welcome to the forum,
Yes, you can finish the course later or go through the course at a slower pace. We prioritize the assignment/project evaluations of live courses so if the deadline is ignored there may be some delay from our side to evaluate the assignments.
Thanks and Regards.

1 Like