Target audience
- Python programmers
- Peeps who want to enter data science as a profession
Participating as a Student
Pre-requisites
The Lisbon Data Science Starters Academy is for [spoiler alert…] Starters!
No prior knowledge of Data Science is required, but we do require:
- Fluency in English (all the classes and materials will be provided in English),
- Comfort with the Python programming language,
- Knowing how to use the command line of a Unix based OS, and
- [super-basic] Git knowledge
Quantitative skills are highly encouraged: if you have a good basis of university level algebra and statistics that will definitely help. Mostly the Academy requires the kind of skills that results from having an education or working experience in the fields of (but not only) Engineering, Physics, Mathematics, Management, Economics, etc…
For an idea of whether you have enough skills, consider the following:
Python
You should be able to do the following:
- if and else statements
- for loops
- handle arrays and tuples (including slicing)
- handle lists and dictionaries (including list comprehension)
- string manipulation
- data types (like int, float, string and how to convert variables between them)
- define and use functions
- lambda functions and map
- try except statements
- basics of OOP (like what’s a class, how to instantiate one and use methods from the class)
Unix
Can you cd around? Do you know how to ls and pwd? Do you shiver when you see rm -rf *? You’ll be fine.
Git
You will be expected to use the most frequent Git commands (pull, push, add, commit, checkout) quite frequently, but nothing much more sophisticated. If I’m being completely honest, this is all the Git that most data scientists know, and we seem to get along fine.
English
Are you still here, reading this without some help from your browser’s auto-translate? Then you’re good to go!
Application Process and Acceptance Criteria
We wish to ensure that the students take full advantage of the course. In order to do this, we must filter students to ensure that they (1) have enough skills to keep up with the coursework and (2) do not already have deep knowledge in all subject matter.
Students have to pass a coding test in Python and solve three learning units. Cheaters will be caught and feathered.
Who should apply
- Technical professionals who want to break into the wonderful world of Data Science
- Students of technical fields who wish to make data science their first job
- Technically minded people with little formal training but who are strong self-learners (we check skills, not CVs)
Who should not apply
- People who do not have a comfortable working knowledge of Python. You’ll be frustrated, bored, and we won’t be able to help you with basic code questions. If you aren’t familiar with Python we suggest doing the wonderful Codecademy Python Course or our Python Prep Course.
Cost to students
While not a profit-making organization, the Academy is not free - to pay for the infrastructure cost, to ensure that it is sustainable in the long-term, and that the students are committed to the learning experience. The fees are much lower than with for-profit initiatives, as the teaching staff are volunteers. All revenues are re-invested into future editions of the Academy, or donated to Python-based open source initiatives.
Code of Conduct
The Academy operates under a strict Code of Conduct, based on documents by Coursera and Pydata. Please read the Code of Conduct in full before applying.
Volunteering
Check out the Membership Types in the LDSA Charter doc to see what is available.