What will I learn?
The online probability and data science course (in its free or paid mode), Data Science: Probability introduces you to the basics and applications of probability theory, the branch of mathematics that deals with uncertainty and randomness. This course offers a comprehensive exploration of probability theory and its applications in analyzing and interpreting data. You will learn how to define and calculate probabilities, how to use probability distributions and models, and how to apply probability theory to data analysis and inference.
This course is designed for anyone who wants to learn the essential skills and tools for data science. Whether you’re a beginner in data science or a seasoned professional looking to enhance your skills, this course provides valuable insights and practical knowledge to help you excel in the field. The course is a game-changer for aspiring data scientists and anyone interested in understanding the role of probability in data analysis. You will need some basic knowledge of algebra, calculus. The course has a rigorous and didactic approach, which combines clear and simple explanations with examples and activities that will help you consolidate your learning. The course also offers you additional resources, such as readings, videos and links of interest, that you can consult to expand your knowledge and deepen the topics that interest you the most.
This course is available on the edX platform, one of the world’s most prestigious online education platforms, founded by MIT and Harvard University. It can be taken completely free of charge or for a small fee.
Contents of the online probability and data science course, Data Science: Probability
These are the contents of the course:
- Probability basics: how to use the axioms and rules of probability, how to use conditional probability and Bayes’ theorem, and how to use combinatorics and counting techniques.
- Probability distributions: how to use discrete and continuous probability distributions, such as the binomial, Poisson, normal, exponential, and uniform distributions, and how to use the mean, variance, and standard deviation to describe and compare distributions.
- Probability models: how to use joint, marginal, and conditional distributions, how to use independence and correlation, and how to use the law of large numbers and the central limit theorem.
- Probability applications: how to use probability theory to perform data analysis and inference, such as hypothesis testing, confidence intervals, and Bayesian inference, and how to use probability theory to understand and evaluate machine learning algorithms, such as classification, regression, and clustering.
Free or paid probability and data science course
The course has two modalities: free and paid. The free probability and data science course allows you to access all the content of the course, including the videos, the readings, the exercises and the discussion forums.
The paid modality also offers you the possibility of obtaining a verified certificate from edX, which accredits your participation and approval of the course. This certificate can be of great value for your curriculum vitae, as it demonstrates your interest and competence in probability and data science. In addition, by paying for the course, you will be contributing to Harvard University and edX being able to continue offering quality and accessible courses for everyone. If you want to know more about the cost and benefits of this modality, I invite you to visit the course page on edX, where you will find all the information you need.
In conclusion, the online probability and data science course (in its free or paid mode), Data Science: Probability, will make you appreciate and enjoy the power and beauty of probability theory, and help you develop critical thinking and problem-solving skills. Don’t miss this opportunity and enroll today!
