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Many courses could teach you the basics of data science, but Harvard University is undoubtedly at the top. Coming from an elite university, all of their courses certainly provide you with the skills needed to become a data scientist.
So what are these free courses you should know about?
Let's get into it.
HarvardX: CS50 Introduction to Python Programming
Python is the key to employment for any aspiring data scientist.
Data scientists are expected to understand the programming languages of the modern era. Python is a de facto language used in many industries, so it is beneficial to learn it.
HarvardX: CS50 Introduction to Python Programming would teach you the core Python programming language needed as a data scientist. In this course we would learn the following:
- Functions, variables
- Conditionals
- Loops
- Libraries
- Unit exam
And many more things that you would learn in ten weeks if you dedicate between 3 and 9 hours a week. You should start with this free Harvard course before entering any other course, as many data science courses after this depend on your ability to use Python.
HarvardX: Fat Chance: probability from scratch
For data scientists, it is important to understand the basics of statistical probability as they relate to our work. To improve your quantitative reasoning skills, the HarvardX: Fat Chance: probability from scratch The course is perfect to develop that knowledge.
In this course, you will review material that will increase your understanding of probability and statistics, such as:
- Basic and advanced counting.
- Basic and conditional probability
- Expected values
- Bernoulli trials
- Normal distribution
The course is designed for self-paced learning and takes considerably around seven weeks to complete if you spend 3-5 hours per week learning.
HarvardX: Introduction to Data Science with Python
Once you have the basics of Python and probability, it's time to learn about data science. He HarvardX: Introduction to Data Science with Python It would teach you the fundamentals needed to enter the field of data science.
It is a self-paced course, but requires a basic understanding of Python and probability. That is why it is important to finish the two previous courses.
The course can be completed in 8 weeks if you spend between 3 and 4 hours a day and you will learn the following:
- Linear, multiple and polynomial regression
- Model selection and cross-validation
- Bias, variance and hyperparameters
- Classification and logistic regression
- Bootstrap, confidence intervals and hypothesis testing
There are many things you will learn from this course. Learn well; The base would be important for the next course.
HarvardX: Machine Learning and artificial intelligence with Python
If you already have the basic knowledge of data science, it's time to learn a more advanced field. Machine learning and artificial intelligence are inseparable from data science, as many enterprise data science projects are based on machine learning results.
Machine learning and ai insights are valuable in the industry as they could uncover patterns we haven't seen before while also providing automation. This could make businesses run much more efficiently than standard decision making based on rules or feelings.
He ai-with-python” target=”_blank” rel=”noopener”>HarvardX: Machine Learning and artificial intelligence with Python The course would give the student a basic understanding of machine learning and ai, including:
- Machine learning models
- Model training
- Model evaluation
- Python for machine learning models
With an estimate of six weeks to complete, if you spend 4-5 hours a week, you will be ready to develop your first data science project.
Conclusion
The Harvard courses we've explored will help you become a data scientist.
By shaping their foundation, all these courses will guide the aspiring data scientist towards their dream careers.
There may only be four courses listed, but these four are the only ones you need to develop the basics.
Cornellius Yudha Wijaya He is an assistant data science manager and data writer. While working full-time at Allianz Indonesia, he loves sharing data and Python tips through social media and print media. Cornellius writes on a variety of artificial intelligence and machine learning topics.
