Course overview

Over the last few years, many people have wanted to but not been able to get into the LDSSA. As of now, we have not been able to offer them any community-based alternatives which leaves them with the usual options of lonely online courses. While the course material, grading system, and access to instructors are definitely useful things, the vast majority of the value provided to the students is in the community aspect. The feeling that you’re not going it alone is incredibly powerful.

Since 2020, we have started to offer the LDSA Unofficial Sidecar Academy, a community-based lightweight version of the LDSA and is meant to provide all of those who didn’t have a chance to get into the 2020 LDSSA, a concrete next step in their pursuit of Data Science. Proficiency in Python, and basic knowledge of Software engineering is required to adequately follow the learning materials.

It should not be mistaken for the Lisbon Data Science Academy (LDSA), or the Lisbon Data Science Starters Course (LDSSA).

Structure

The Sidecar Academy lasts approximately 30 weeks of part-time work over the course of 8 months. Everything is done remotely via GitHub, Slack, and the grading and submission system. You do not need to quit your primary responsibility to take part in this course.

The curriculum can be referenced via the curriculum-development repo

Time Commitments

You should be prepared to spend a recommended 10 hours per week on the course and an absolute minimum of 5 hours per week in case you are having a busy week.

What will be covered

In the Unofficial Sidecar Academy, we will go through the same materials of Lisbon Data Science Starters Academy (LDSSA).

All of the learning units, all of the exercises, all of the recorded lectures (if there’s any) will be 100% the same. So make sure that you head over Lisbon Data Science Starters Academy (LDSSA) to understand how the course is structured.

In short, we will be using Learning Units as our main method of coursework. Two main types of Learning Units are:

Small Learning Units: consists of (1) A presentation (2) A Learning Notebook (3) An example notebook and (4) An exercise notebook
Big Learning Units: consists of (1) 3 Learning Notebooks (2) An exercise notebook

What is the same and what is different

While the Sidecar Academy will share the same materials as LDSSA, there are a few important differences as follows:

There will be a different community. Many of the instructors that are available on the LDSSA will not be directly available in the Sidecar Academy.
The students will need to help each other a LOT. Since there will be less instructors available, this is a necessity.
It will be completely free and remote.
The feedback is provided through the material’s self-grading system so students will need to keep track of their progress autonomously
There will not be bootcamp nor final capstone project
Hackathons will follow a format similar to Kaggle-style challenges (More details in section below)

Introduction session

The introduction session is an online session that kicks off the Sidecar academy, which will take place on the 24th of October at 3pm. In this session all rules and schedule present in this page will be presented, together with any practical details for the current edition.

Additionally we will go over and answer any questions related to the following topics:

Course structure
Code of Conduct
How to ask for and give help
Hackathons

Please keep in mind that this session is not compulsory. Nonetheless, we encourage you to participate and get to know the staff behind the course and the fellow students who will be with you in this 8-month journey.

Hackathons

Each Hackathon will take place during three days. A few days prior to the starting date a form will have to be filled to confirm the interest in participating in each Hackathon. Teams will be randomly assigned based on the number of participants.

Once you are assigned with a team, it is up to you and your fellow teammates to organise yourself into working together and solving the problems through joint effort. Teams should submit their results to a Kaggle competition that will be created by the LDSA team. A classification table will also be available to compare the various approaches to the problem. Every team is encouraged to post their solution notebook at the end of each Hackathon.

Schedule

The master schedule google calendar is here! You can add this calendar to most calendar apps so that you can be sure that you stay aware of all the important dates.

Late policy

If something happens and you could not follow the deadline, you can still ask questions about the previous week’s SLU. Just remember to post it in the right Slack channel!

Frequently Asked Questions (FAQ)

1. I just want to check that the whole course is 100% remote right?

Everything is 100% remote and online!

2. Will you offer any certificate at the end of the course?

No certificate will be given. However, we are sure that, more than the certificate you could get, your biggest takeaway from this course will be the knowledge you’ve acquired and how it will help you navigate the world of Data Science.