**Course Description**

Are you studying for your first actuarial exam? Do you want to one day work as an Actuary, which is consistently ranked as a top 10 career?

Well then, you’ve come to the right place!

This is where you start. And it is the perfect time to start. Actuaries are in high demand globally. Actuaries can earn a great living and enjoy great job satisfaction.

To become a fully qualified actuary, you have to pass a series of professional exams. Most students start by taking a related university degree. This course along with Part 2 to the course, will provide you with the skills required to pass the first actuarial exam.

Whether you are writing with the Society of Actuaries (SOA) or Casualty Actuarial Society (CAS), this course is for you. The material for SOA Exam P or CAS Exam 1 is covered in this course and Part 2 to this course.

**Part 1 will cover the following areas of the exam:**

- Set Theory, Sample Spaces and Probability Spaces
- Basic Probability Theory
- Counting Problems, Permutations and Combinations
- Conditional Probability and Independent Events
- Bayes' Rule and the Total Law of Probability
- Discrete and Continuous Random Variables
- Probability Density Function (PDF), Cumulative Distribution Function (CDF) and Survival Functions
- Expected Values, Higher Moments, Variance, Standard Deviation and Coefficient of Variation
- Percentiles, Median and Mode
- Mixed Distributions
- Moment Generating Functions (MGFs) and Probability Generating Functions (PGFs)
- Frequently Used Discrete Distributions
- Frequently Used Continuous Distributions

Practice makes perfect with actuarial exams. As such, we have included many practice problems for you to hone your skills. The SOA also provides sample questions and we highly recommend that you practice your skills on these questions as well.

**Teaching is my passion!**

I have been teaching actuaries around the world since 2014 and have helped 100s of actuaries pass actuarial exams. I have also taught at the University level, teaching courses on probability and mathematical statistics. My teaching style focuses on explaining concepts and then illustrating those concepts with lots of examples. I find that this allows the students to understand the basics and then directly tie the theory to practical applications with practice problems. This sets the students up for success with the actuarial exams that they intend to write.

**Why take this course?**

This course (along with Part 2) is designed to cover the SOA Exam P/CAS Exam 1 syllabus in entirety. This course is specifically tailored to the actuarial exam. There are a lot of other courses that teach probability and statistics, however, they are more general in nature, whereas this course focuses exclusively on getting you to a passing grade come exam day. My course also offers you lifetime access to the material and was priced at a price point that would be affordable to students around the world.

**What you get with this course?**

You get access to over 10 hours of video lectures that cover the entire syllabus, split between Part 1 and Part 2. You also get access to an electronic manual for the course and over 100 practice questions to hone your skills and prepare you for the actual exam day.

**Example Curriculum**

- Lecture 4: Set Theory (10:11)
- Lecture 5: Sample Spaces (or Probability Spaces) and Venn Diagrams (20:56)
- Lecture 6: Basic Probability Models (27:05)
- Lecture 7: Counting Problems, Permutations and Combinations (37:51)
- Lecture 8: Conditional Probability (22:45)
- Lecture 9: Independent Events (16:12)
- Lecture 10: Bayes' Rule and Total Law of Probability (32:47)

- Lecture 11: Introduction to Random Variables (2:22)
- Lecture 12: Discrete Random Variables (34:07)
- Lecture 13: Continuous Random Variables (12:45)
- Lecture 14: Survival Functions and Hazard Rates (3:57)
- Lecture 15: Expected Values and Other Statistics (50:38)
- Lecture 16: Percentiles, Median and Mode (17:37)
- Lecture 17: Mixed Distributions (26:09)
- Lecture 18: Moment Generating Functions (23:18)
- Lecture 19: Probability Generating Functions (9:03)

- Lecture 20: Discrete Uniform Distribution (17:21)
- Lecture 21: Bernoulli Distribution (3:00)
- Lecture 22: Binomial Distribution (26:40)
- Lecture 23: Geometric Distribution (19:38)
- Lecture 24: Negative Binomial Distribution (16:59)
- Lecture 25: Poisson Distribution (29:58)
- Lecture 26: Hypergeometric Distribution (14:44)
- Lecture 27: Advanced Topics (10:15)