Probability and Statistics for Business and Data Science course covers all you need to know about statistics and probability to thrive in business and the field of data science. This hands-on course will cover statistical theory and how to apply it to issues in the real world. There are assessment examinations, in-course quizzes, and example problems in every section. The most prevalent statistical distributions will then be covered, giving the students a firm understanding of how to work with the uniform, binomial, Poisson, and normal distributions.
The remaining three sections of the course will cover advanced concepts like chi-squared analysis, regression analysis, and ANOVA (analysis of variance). Because the sections are modular and arranged by subject, students can quickly find what they need and get started. The course features HD Video with understandable explanations and top-notch animations, as well as in-depth case studies that demonstrate how to use this information in the real world. Currently, udemy is offering the Probability and Statistics for Business and Data Science course for up to 87 % off i.e. INR 449 (INR 3,499).
Who can opt for this course?
- Someone who wants to learn how to use statistics and probability in data science or business
Course Highlights
| Key Highlights | Details |
|---|---|
| Registration Link | Apply Now! |
| Price | INR 449 ( |
| Duration | 05 Hours |
| Rating | 4.6/5 |
| Student Enrollment | 29,873 students |
| Instructor | Jose Portilla https://www.linkedin.com/in/joseportilla |
| Topics Covered | Measurements of Central Tendency, Intersections, Unions, Complements, Addition, and Multiplication Rules |
| Course Level | Intermediate |
| Total Student Reviews | 5,702 |
Learning Outcomes
- Know the fundamentals of probability
- Be able to use fundamental statistics
- Know how to apply different statistical distributions
- To solve business problems, use statistical techniques and hypothesis testing
- Recognize the operation of regression models
- Use the ANOVA in one and two dimensions
- Recognize Chi-Square tests
- Being able to comprehend various data kinds
Course Content
| S.No. | Module (Duration) | Topics |
|---|---|---|
| 1. | Introduction (05 minutes) | Course Overview Lecture – PLEASE DO NOT SKIP THIS! |
| FAQ – Frequently Asked Questions | ||
| 2. | Data (01 hours 00 minutes) | What is Data? |
| Measuring Data | ||
| Quiz #1 – Measuring Data | ||
| Measurements of Central Tendency | ||
| Quiz #2 – Measures of Central Tendency | ||
| Measurements of Dispersion | ||
| Quiz #3 – Measures of Dispersion | ||
| Measurements – Quartiles | ||
| Quiz #4 – Quartiles and IQR | ||
| Bi-variate Data and Covariance | ||
| Pearson Correlation Coefficient | ||
| Section Assessment – Data | ||
| 3. | Probability (52 minutes) | What is Probability? |
| Permutations | ||
| Quiz #5 – Permutations | ||
| Combinations | ||
| Quiz #6 – Combinations | ||
| Intersections, Unions, and Complements | ||
| Independent and Dependent Events | ||
| Quiz #7 – Independent & Dependent Events | ||
| Conditional Probability | ||
| Quiz #8 – Conditional Probability | ||
| Addition and Multiplication Rules | ||
| Bayes Theorem | ||
| Quiz #9 – Bayes Theorem | ||
| Section Assessment – Probability | ||
| 4. | Distributions (55 minutes) | Introduction to Distributions |
| Uniform Distribution | ||
| Quiz #10 – Uniform Distribution | ||
| Binomial Distribution | ||
| Quiz #11 – Binomial Distribution | ||
| Poisson Distribution | ||
| Quiz #12 – Poisson Distribution | ||
| Normal Distribution | ||
| Quiz #13 – Normal Distribution | ||
| Normal Distribution – Formulas and Z Scores | ||
| Quiz #14 – Z Score | ||
| Section Assessment – Distributions | ||
| Optional Resource – Dash Scripts | ||
| 5. | Statistics (01 hour 08 minutes) | What is Statistics? |
| Sampling | ||
| Central Limit Theorem | ||
| Quiz #15 – Sampling and CLT | ||
| Standard Error | ||
| Hypothesis Testing | ||
| Hypothesis Testing Example Exercise #1 | ||
| Hypothesis Testing Example Exercise #2 | ||
| Quiz #16 – Hypothesis Testing #1 | ||
| Type 1 and Type 2 Errors | ||
| Quiz #17 – Hypothesis Testing #2 | ||
| Student’s T Distribution | ||
| Student’s T Distribution Example Exercise | ||
| Section Assessment – Statistics | ||
| 6. | Analysis of Variance (ANOVA) (34 minutes) | Introduction to ANOVA |
| ANOVA – Analysis of Variance | ||
| F Distribution | ||
| Two-Way ANOVA Overview | ||
| Two-Way ANOVA Example Exercise | ||
| Two Way ANOVA with Replication | ||
| Section Assessment – ANOVA | ||
| 7. | Regression (24 minutes) | Linear Regression |
| Regression Example | ||
| Multiple Regression | ||
| Section Assessment – Regression | ||
| 8. | Chi-Square Analysis (12 minutes) | Chi-Square Analysis |
| Chi-Squared Analysis – Exercise Example | ||
| Section Assessment – Chi-Square Analysis | ||
| 9. | BONUS SECTION: THANK YOU! (10 seconds) | BONUS LECTURE |
Resources Required
- A pencil and paper for taking notes
- Excel or Python are optional for doing simulations
Featured Review
Anonymized User (5/5): Absolutely amazing course!!! This course gives an in-depth knowledge of Statistics and Probability required for Data Science and Machine Learning. Content-wise it is very detailed-oriented and has been divided into small segments to keep it structured as well as easy to understand. Jose’s teaching methodology is outstanding specifically in this course, he tried to solve real-life statistical problems and I liked almost all of his courses including Python for Data Science and ML Bootcamp + Python for Computer Vision and Deep Learning. By completing this course, I am proud to say this is Highly Recommended for aspiring Data Scientists and Machine Learning Engineers.
Pros
- Adam Weissman (5/5): I wish I could give 6 stars, and that there were a sequel to this course because it is the very best.
- JL Rosas (4/5): Its choice of, in some cases, just Excel examples (instead of Python), was not the best one in my opinion.
- Fernando Souza Soares (5/5): Thank you Jose for another great course! You never disappoint me!
- Shreyashi Mukhopadhyay (5/5): Jose has done an excellent job with the content and explanation of every module.
Cons
- Rüzgar Pala Üçkarde? (2/5): Even though I know the subject of probability, I had a hard time understanding this issue from these slides.
About the Author
The instructor of this course is Jose Portilla who is a Head of Data Science at Pierian Training with a 4.6 instructor rating and 977,223 reviews on Udemy. He offers 57 Courses and has taught 3,142,403 Students so far.
- Jose Marcial Portilla holds degrees in mechanical engineering from Santa Clara University (BS and MS), and he has years of experience working as a qualified instructor and trainer for Python programming, machine learning, and data science
- He has written articles and received patents in a number of disciplines, including data science, materials science, and microfluidics
- He has acquired a set of abilities for data analysis throughout the course of his career, and he wants to combine both his teaching and data science knowledge to educate others the power of programming, how to analyze data, and how to display the data in attractive visualizations
- He currently serves as the Head of Data Science for Pierian Training, where he trains people at prestigious organizations like General Electric, Cigna, The New York Times, Credit Suisse, McKinsey, and others in data science and python programming on-site
Comparison Table
| Parameters | Probability and Statistics for Business and Data Science | Become a Probability & Statistics Master | Statistics for Data Science and Business Analysis |
|---|---|---|---|
| Offers | INR 455 ( | INR 455 ( | INR 455 ( |
| Duration | 5 hours | 14.5 hours | 5 hours |
| Rating | 4.6 /5 | 4.7 /5 | 4.6 /5 |
| Student Enrollments | 29,872 | 72,839 | 160,317 |
| Instructors | Jose Portilla | Krista King | 365 Careers |
| Register Here | Apply Now! | Apply Now! | Apply Now! |
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