Why build projects in Python and R?
People don’t pay you for what you know. They pay you for the solutions you build to solve their problems.
|Video Tutorials||Programming Books||Project-based Learning|
|Passive||Passive||Very Active Learning|
|Mid to High Retention||Programming Books||Highest Retention|
|Mixed||Mostly Principles / Theoretical||Practical, Real-life projects|
|Mixed||Mostly narrowly scoped||Widely scoped*|
I’ve written plenty of programming articles, course books, and made video tutorials related to R and Python programming over the last many years. I guest-lecture actively, and run a programming bootcamp with 3 active campuses across Singapore and Indonesia. My courses and even taught in curriculums offered by universities and polytechnics.
The same time that I was authoring courses, I started to study learning performance and pedagogical approaches, building open-source systems to measure and quantify knowledge absorption based on the different teaching styles.
The winner was clear to me: people learn programming the way they learn swimming.
You have to do it.
I can play you hundreds of hours worth of videos, of an Olympic swimmer doing her routines, but that’s not going to turn you into a swimmer. The way to learn, as cliche as it sounds, is to get into a pool. No alternatives, non-negotiable.
The same is true for programming (and singing, engineering, playing the piano etc). The best pianists spend hours on the pianos on long stretches. Not on a couch watching videos of world-class musicians.
There simply aren’t any substitute to active learning.
I started Fine Tutorials to double-down on project-based learning. Forget about 30% video, 30% reading, 30% hands-on programming, 5% quiz and 5% quiz; What if I tutor you through the process of building end-to-end projects from day 1 of you learning programming. Your own projects.
It’s more rewarding to learn programming this way, but it’s also advantageous in ways that theory-heavy books or lectures cannot be.
Learn-by-building helps cultivate:
New to Programming?
Start with the Data Science Toolbox if you’re completely new to programming (in particular Python and R Programming). It has a very gentle learning curve, walking you through the steps required to get your computer configured for Python, R, git (version control) and GitHub (hosting, version control) integration, as well as using the various programming editors:
- Basic usage of the command prompt and Terminal
- Visual Studio Code
- JupyterLab (+ Jupyter Notebook)
The full course is free and have no prerequisites.
Who creates the courses on Fine Tutorials?
Hello, I’m Samuel.
I’m also the chief course producer at Algoritma (https://algorit.ma) Data Science Education Centre, where I’ve authored consultative training for more than 200 companies in Southeast Asia (primarily Singapore, Indonesia, Thailand and Malaysia) and taught data science to more than 10,000 students across the region. I guest-lecture regularly in more than 10 universities + polytechnics across Singapore and Indonesia on:
- Machine Learning
- Deep Learning and Computer Vision
- Natural Language Processing (English and Bahasa Indonesia)
- Data Visualisation
- Web Application Development
- Cybersecurity and Network Monitoring
You can also connect with me on LinkedIn:
More than 10,000 students
Prefer video testimonials?
The data science education centre that I co-founded has worked with more than 200 companies, and we have 120+ testimonial videos on YouTube. Most of these videos are in the student’s native tongue (Indonesian, Thai etc) but among them you will find testimonial videos from companies that are household names in the United States, including OCBC, UOB, United Tractors and Citibank just to name a few. You can use an online translation service such as Google Translate to hear what my students say about the level of quality and care we put into our training.
Why Python and R, specifically?
What edge does Python or R have over the other programming languages?
Python and R are two of the fastest growing languages according to polls by TIOBE, StackOverflow and even search data by Google Trends. Python is even the most wanted programming language for three years in a row (as of end 2019).
This is even more impressive when you consider the earning potential for these 2 languages. In the same survey by StackOverflow, Data scientist or machine learning specialist are the 4th highest paid ($61k global median, $120k US median), slightly behind data engineers ($66k global median, $120k US median) and followed by Data analyst ($59k global median, $100k US median). Python and R programming are the main tools in any data science work.
Don’t just be employable
Learn the skills that will be the most sought after in the market right now (and will continue to be so for the next 5 years).
What’s the catch? It’s that companies generally don’t pay you for what you know. They pay you for the problems you can solve. In other words, they pay you for the solutions you build to solve their problems. The single fastest way to develop this ability is — you guessed it — to build.
Ready to take your first step?
Build a web app in R
A beginner-friendly introduction to R programming, practical data processing, data visualization techniques and Shiny web application development.
Audit the Course
The first 4 lessons are free, and present a good idea of the project we’ll be building. Between the 4 lessons here and the 13 lessons in the free Data Science Toolbox course, there are 17 tutorials in total provided to you, free of charge. If you decide to support me by purchasing the course, you’ll get support to both of these courses.
Purchase the Course
Still have questions? Email me: samuel.c[at]outlook<dot>com.