1. Wrapping up
Congratulations, you made it to the end of the course!!
We've covered a lot of ground.
2. Fundamental concepts
We learned to simulate random variables in order to review the fundamental concepts of probability, such as density, distributions, expected values, sample means, variance, joint probability of dependent and independent events, and conditional probability using Bayes' rule.
3. Important probability distributions
We reviewed some of the most important probability distributions, such as binomial, geometric, Poisson, and normal distributions.
4. The most important results
We also studied the most important laws of probability: the law of large numbers and the central limit theorem.
5. Linear and logistic regression
Finally, we applied those concepts in data science and reviewed linear regression and logistic regression, fitting models, and predicting.
There's a lot more to study, and other DataCamp courses go into much more depth on many of the topics we've covered.
6. Keep learning at DataCamp!
To really understand and get to grips with all the methods you've seen in this course, it's important to apply them with real data. Only with practice will you truly master the content.
By relating these methods to real-life situations you can gain a deeper understanding about your context with science.
There are many more courses at DataCamp you can work through to deepen your understanding about probability and statistics.
Keep going and good luck!