Probability

with Viktor Mehandzhiyski
4.8/5
(1,422)

Learn probability fundamentals to think like a data scientist and unlock analytical insights

5 hours of content 30275 students

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 5 hours of content
  • 97 Interactive exercises
  • 19 Downloadable resources
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

Probability

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 5 hours of content
  • 97 Interactive exercises
  • 19 Downloadable resources
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

$99.00

Lifetime access

Buy now

$99.00

Lifetime access

Buy now
14-Day Money-Back Guarantee

What you get:

  • 5 hours of content
  • 97 Interactive exercises
  • 19 Downloadable resources
  • World-class instructor
  • Closed captions
  • Q&A support
  • Future course updates
  • Course exam
  • Certificate of achievement

What You Learn

  • Acquire foundational knowledge in probability theory
  • Become familiar with key probability terms and ideas
  • Explore the practical applications of probability theory
  • Be able to determine what kind of distribution a dataset follows
  • Learn how to describe events and analyze their interactions
  • Use and interpret Bayesian notation

Top Choice of Leading Companies Worldwide

Industry leaders and professionals globally rely on this top-rated course to enhance their skills.

Course Description

Data science is based on statistics which, in turn, steps on the foundations that probability laid out. Learning probability is arguably one of the most crucial skills for success in the business world. The reason is that developing probabilistic thinking and being able to assess risks and possible outcomes are key skills business executives need to navigate an uncertain environment. So, congratulations, you have come to the right place. If you take this probability course, you will acquire a probabilistic mindset - a critical skill when making strategic decisions and solving complex problems. Our probability class will teach you how to analyze data effectively and make predictions with confidence. You'll learn to apply probability models to real-world situations, enabling you to interpret and manage the uncertainties that define today's business landscape. Probability is not difficult. Once you are inside our probability course, you will see that for yourself. We will not ask you to read hundreds of pages of dry theory or provide a random collection of PowerPoint slides. Instead, the videos we’ve created are engaging, practical, concise, and most importantly fun to watch. We leverage storytelling and real-world examples to ensure you will watch until the end of the course. The interactive exercises in our probability training will ensure that you have a chance to practice what has been explained in the lessons hands-on. This course is the best way to learn probability and ensure you will get the desired results. This probability course is suitable for university students who need probability for their studies. It is also highly recommended for graduates and young professionals who want to improve their decision-making and quantitative skills. Even if you haven’t learned any probability before, don’t worry. This intro to probability course is designed to guide you from the ground up. Join us on a journey that will introduce you to combinatorics, Bayesian inference, and the different types of distributions. Gain the quant skills to use inferential statistics and work with the normal distribution. By completing the course, you will be able to use the Bayes theorem and calculate probabilities with confidence. How is this probability for data science course different than the rest? 1. Content quality The course instructor and our team have spent months of research and prep work to create an optimal curriculum that ensure everything you see in the probability course is necessary and useful. Our step-by-step approach ensures you will be able to understand and apply probability concepts confidently. Through a blend of theoretical knowledge and practical exercises, you will develop a sold understanding of probability. 2. Downloadable materials Gain access to valuable downloadable resources you can always use as a reference. The course comes with a full set of materials – complete probability course notes, flashcards with key terms, practice exercises, course exams – everything is included inside. 3. Certificate of achievement If you compete the Probability course and pass successfully its course exam, you will be awarded a verifiable certificate of achievement, which is a testament to your dedication and hard work. Click the ‘Buy now’ button and start this amazing learning journey today! Make an investment to acquire probability and decision-making skills that could change your entire career.

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Course Introduction

1.1 Course Introduction

3 min

What is the Probability Formula

1.2 What is the Probability Formula

7 min

Expected Values

1.4 Expected Values

5 min

Probability Frequency Distribution

1.6 Probability Frequency Distribution

5 min

Complements

1.8 Complements

5 min

Fundamentals of Combinatorics

2.1 Fundamentals of Combinatorics

1 min

Curriculum

  • 1. The Basics of Probability
    5 Lessons 25 Min

    In this part of the Probability for data science course, we explore why probability is fundamental to becoming a data scientist. We introduce you to the key terms and ideas concerning probabilities and events, including theoretical and experimental probabilities, preferred outcomes, sample space, expected value, and complements.

    Course Introduction
    3 min
    What is the Probability Formula
    7 min
    Expected Values
    5 min
    Probability Frequency Distribution
    5 min
    Complements
    5 min
  • 2. Combinatorics
    12 Lessons 44 Min

    This section is designed to teach you what combinatorics is and where we encounter it in life. We will consider the three central concepts in combinatorics – permutations, variations, and combinations – and you’ll learn how to calculate each of these with the correct formulas.

    Fundamentals of Combinatorics
    1 min
    Computing Permutations
    3 min
    Solving Factorials
    4 min
    Variations with Repetition
    3 min
    Variations without Repetition
    4 min
    Combinations without Repetition
    5 min
    Combinations with Repetition Read now
    1 min
    Symmetry of Combinations
    3 min
    Combinations with Separate Sample Spaces
    3 min
    Winning The Lottery
    3 min
    Summary of Combinatorics
    3 min
    Practical Example - Combinatrics
    11 min
  • 3. Bayesian Inference
    12 Lessons 54 Min

    Here you will learn how to describe events and the ways they interact with one another. We introduce important concepts like intersections, unions, and conditional probability. Then we focus on Bayes’ Law and how to use it to interpret the relationships between the possible outcomes of various events.

    Sets and Events
    4 min
    The Different Ways Events Can Interact
    4 min
    The Intersection of Two Sets
    2 min
    The Union of Two Sets
    5 min
    Mutually Exclusive Sets
    2 min
    Dependent and Independent Events
    3 min
    Conditional Probability
    4 min
    Law of Total Probability
    3 min
    Additive Law
    2 min
    Multiplication Rule
    4 min
    Bayes Rule
    6 min
    Practical Example - Bayesian Inference
    15 min
  • 4. Discrete Distributions
    7 Lessons 33 Min

    In this section of the probability for data science course, you will learn to determine what kind of distribution a dataset follows. This is crucial in making accurate predictions about the future. We talk about the possible values a random variable can take and how frequently they occur. We introduce well-known distributions and events that follow them, and then proceed to discuss each common distribution in greater detail.

    An Overview of Distributions
    6 min
    Types of Distributions
    8 min
    Discrete Distributions
    2 min
    Uniform Distribution
    2 min
    Bernoulli Distribution
    3 min
    Binomial Distribution
    7 min
    Poisson Distribution
    5 min
  • 5. Continuous Distributions
    8 Lessons 41 Min

    Here, you will build upon the probability distributions knowledge you developed in the previous section of the probability class. We review several of the most widely encountered continuous distributions and discuss how to determine them, where they are applied, and how to apply their formulas.

    Continuous Distributions
    7 min
    Normal Distribution
    4 min
    Standardizing a Normal Distribution
    4 min
    Students T Distribution
    2 min
    Chi-Squared Distribution
    2 min
    Exponential Distribution
    3 min
    Logistic Distribution
    4 min
    Practical Example - Distributions
    15 min
  • 6. Probability in Other Fields
    3 Lessons 18 Min

    In this section, we spend a minute exploring the tie-ins between this field and several others, such as finance, statistics and data science.

    Probability in Finance
    8 min
    Probability in Statistics
    6 min
    Probability in Data Science
    4 min

Topics

probabilityCombinatoricsBayesian InferenceBayes TheoremProbability Distributions

Tools & Technologies

excel

Course Requirements

  • No prior experience or knowledge is required. We will start from the basics and gradually build your understanding. Everything you need is included in the course.

Who Should Take This Course?

Level of difficulty: Beginner

  • People who want to improve their decision-making skills
  • Aspiring data analysts, data scientists, business analysts
  • Graduate students who need probability for their studies
  • Business executives who are passionate about developing a probabilistic mindset

Exams and Certification

A 365 Data Science Course Certificate is an excellent addition to your LinkedIn profile—demonstrating your expertise and willingness to go the extra mile to accomplish your goals.

Exams and certification

Meet Your Instructor

Viktor Mehandzhiyski

Viktor Mehandzhiyski

Data Scientist at

3 Courses

2972 Reviews

64518 Students

A Hamilton College graduate, Viktor has a strong analytics background, focusing on the fields of Statistics, Econometrics, Financial Time-Series Econometrics, and Behavioral Economics. Viktor’s coding experience is rather diverse – from working with C, C++, and Python through to the more math/econ-oriented MATLAB and STATA. He has been fascinated by coding algorithms since the age of 11 and describes himself as a “Bachelor of Science and overall cool guy”. We couldn’t agree more. Some of Viktor’s personal achievements include developing a model for forecasting transfer prices of soccer players across Europe’s top divisions and Stock Market Indexes analysis on the effects of contagion on the effectiveness of international portfolio diversification.

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