09.10.2024
Probability
with
Viktor Mehandzhiyski
Learn probability fundamentals to think like a data scientist and unlock analytical insights
5 hours of content
27022 students
20% off : : :
Get 20% OFF
$99.00
$79.00
00 Days
18 Hours
49 Minutes
27 Seconds
14-Day Money-Back Guarantee
What you get:
- 5 hours of content
- 19 Downloadable resources
- Interactive exercises
- World-class instructor
- Closed captions
- Q&A support
- Future course updates
- Course exam
- Certificate of achievement
Probability
A course by
Viktor Mehandzhiyski
20% off : : :
Get 20% OFF
$99.00
$79.00
00 Days
18 Hours
49 Minutes
27 Seconds
14-Day Money-Back Guarantee
What you get:
- 5 hours of content
- 19 Downloadable resources
- Interactive exercises
- World-class instructor
- Closed captions
- Q&A support
- Future course updates
- Course exam
- Certificate of achievement
20% off : : :
Get 20% OFF
$99.00
$79.00
00 Days
18 Hours
49 Minutes
27 Seconds
14-Day Money-Back Guarantee
What you get:
- 5 hours of content
- 19 Downloadable resources
- Interactive exercises
- 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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1.1 Course Introduction
1.2 What is the Probability Formula
1.4 Expected Values
1.6 Probability Frequency Distribution
1.8 Complements
2.1 Fundamentals of Combinatorics
Interactive Exercises
Practice what you've learned with coding tasks, flashcards, fill in the blanks, multiple choice, and other fun exercises.
Curriculum
- 1. The Basics of Probability5 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 Introduction3 minWhat is the Probability Formula7 minExpected Values5 minProbability Frequency Distribution5 minComplements5 min - 2. Combinatorics12 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 Combinatorics1 minComputing Permutations3 minSolving Factorials4 minVariations with Repetition3 minVariations without Repetition4 minCombinations without Repetition5 minCombinations with Repetition Read now1 minSymmetry of Combinations3 minCombinations with Separate Sample Spaces3 minWinning The Lottery3 minSummary of Combinatorics3 minPractical Example - Combinatrics11 min - 3. Bayesian Inference12 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 Events4 minThe Different Ways Events Can Interact4 minThe Intersection of Two Sets2 minThe Union of Two Sets5 minMutually Exclusive Sets2 minDependent and Independent Events3 minConditional Probability4 minLaw of Total Probability3 minAdditive Law2 minMultiplication Rule4 minBayes Rule6 minPractical Example - Bayesian Inference15 min - 4. Discrete Distributions7 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 Distributions6 minTypes of Distributions8 minDiscrete Distributions2 minUniform Distribution2 minBernoulli Distribution3 minBinomial Distribution7 minPoisson Distribution5 min - 5. Continuous Distributions8 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 Distributions7 minNormal Distribution4 minStandardizing a Normal Distribution4 minStudents T Distribution2 minChi-Squared Distribution2 minExponential Distribution3 minLogistic Distribution4 minPractical Example - Distributions15 min - 6. Probability in Other Fields3 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 Finance8 minProbability in Statistics6 minProbability in Data Science4 min
Topics
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.
Meet Your Instructor
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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