Statistics for Data Science & Business Analytics in Python

Focused View

Farzan Sajahan

10:37:30

25 View

1 - Getting started

1 - All-codes-and-datasets.zip

1 - Lets get started Download code and Datasets.html

2 - Quick note.html

2 - Python basics

1 - Quiz Python Basics.html

3 - Installing anaconda distribution and Jupyter.mp4

04:54

4 - Tour of Jupyter notebook.mp4

04:09

5 - Calculations in Python.mp4

07:56

6 - Variables in python.mp4

10:25

7 - Collection data types in python List.mp4

10:18

8 - Collection data types in python continued Tuples Sets and Dictionaries.mp4

11:08

3 - Core programming in Python

2 - Quiz Conditional and logical statements in python.html

3 - Quiz Loops and Functions.html

9 - Conditional and logical statements.mp4

09:42

10 - For and While loops.mp4

05:21

11 - Functions.mp4

05:58

4 - Arrays Matrices and data frames

4 - Quiz numpy.html

5 - Quiz pandas.html

12 - Numpy arrays.mp4

07:00

13 - ndarrays in numpy.mp4

10:47

14 - Access values from a matrix.mp4

07:20

15 - Pandas Series.mp4

08:03

16 - Pandas Data Frames.mp4

14:46

17 - Data frame manipulation.mp4

13:23

5 - Introduction to Statistical Data Analysis

6 - Quiz Introduction to statistical data analysis.html

18 - Introduction to Statistical Data Analysis.mp4

04:57

19 - Variables in Statistical Data Analysis.mp4

01:45

20 - Population Vs Samples.mp4

08:25

6 - Data visualization in python

7 - Quiz data visualization in python.html

21 - One way tables.mp4

12:18

22 - Line Charts and Bar charts.mp4

12:36

23 - Pie Charts.mp4

08:17

24 - Two way cross tables.mp4

05:27

25 - Heat maps.mp4

07:16

7 - Univariate data analysis

8 - Quiz on Univariate analysis.html

26 - Central tendency measures mean median mode.mp4

13:55

27 - Dispersion measures range and interquartile range.mp4

08:50

28 - Histogram.mp4

04:48

29 - Box plot.mp4

06:12

30 - Outliers.mp4

11:16

31 - Variance and Standard deviation.mp4

07:34

32 - Univariate handson exercise.mp4

15:14

8 - Bivariate data analysis

9 - Quiz on Bivariate Analysis.html

33 - Introduction to Bivariate analysis.mp4

18:18

34 - Covariance and Correlation.mp4

11:06

35 - Bivariate handson exercise.mp4

15:20

9 - Probability

10 - Quiz on probability.html

36 - Probability theory.mp4

07:52

37 - Estimating simple probabilities single independent event.mp4

08:22

38 - Estimating probability in case of two or more events.mp4

15:36

39 - Conditional Probability.mp4

09:58

40 - Review the Multiplication law of probability.mp4

10:40

41 - Bayes theorem.mp4

10:05

10 - Random Distributions

11 - Quiz on random distributions.html

12 - Quiz on sampling distributions.html

42 - Random Variables and Probability Distribution.mp4

08:56

43 - Using Probability Distribution to Estimate Probabilities.mp4

08:19

44 - Normal distribution.mp4

09:23

45 - Normal Distribution Handson.mp4

07:27

46 - Tdistribution.mp4

05:23

47 - Finding actual values from the probability.mp4

04:27

48 - Sampling Distribution.mp4

04:39

49 - Central limit theorem handson.mp4

15:01

11 - Hypothesis Testing Test of Means

13 - Quiz on hypothesis testing.html

14 - Quiz on hypothesis testing.html

50 - Introduction to Inferential statistics and hypothesis testing.mp4

07:21

51 - Introduction to test of means.mp4

09:29

52 - Steps for conducting test of means.mp4

08:07

53 - One sample right tail test.mp4

07:30

54 - One sample left tail test.mp4

04:06

55 - One sample two tail T test.mp4

06:32

56 - Two sample unpaired T test.mp4

07:23

57 - Two sample paired T test.mp4

06:23

58 - Errors in hypothesis testing.mp4

05:01

12 - Analysis of Variance ANOVA

15 - Quiz on OneWay ANOVA.html

16 - Quiz on TwoWay ANOVA.html

59 - ANOVA Introduction.mp4

04:05

60 - ANOVA Intuition.mp4

06:38

61 - One Way ANOVA manual computation.mp4

10:07

62 - One Way ANOVA using python.mp4

08:11

63 - Two Way ANOVA case 1 Diet Plan.mp4

16:04

64 - Two Way ANOVA case 2 Movies analysis.mp4

12:21

13 - Test of proportions

17 - Quiz on test of proportions.html

65 - Introduction to test of proportions and independence using Chisquare test.mp4

04:50

66 - Chi square test handson.mp4

08:37

14 - Simple Linear Regression

18 - Quiz on Simple Linear Regression.html

67 - Introduction to Linear Regression.mp4

08:46

68 - Goodness of fit.mp4

04:05

69 - Condition for linear regression.mp4

03:29

70 - Simple Linear Regression Manual method.mp4

08:51

71 - Simple Linear Regression Using OLS package.mp4

14:21

15 - Multiple Linear Regression

19 - Quiz on Multiple Linear Regression.html

72 - MLR case.mp4

10:22

73 - Creating our first MLR model.mp4

09:58

74 - Improving the MLR model.mp4

07:08

75 - Another way to build the MLR model.mp4

06:53

16 - Conclusion

76 - Conclusion.html

Description

Apply Statistics in Real World Business Problems Using Python. Build a Career in Data Science and Business Analytics.

What You'll Learn?

Foundational understanding of python to analyze data using NumPy and Pandas, and use statistical packages such as SciPy and statsmodels.
Analyzing and visualizing data using python using line charts, bar charts, pie charts, histogram and box plots.
Conducting univariate and bivariate analysis using one-way tables, two-way tables.
Descriptive statistics for univariate and bivariate analysis - mean, median, mode, range, IQR, variance, standard deviation, covariance and correlation.
Data distributions, including mean, variance, and standard deviation, T-distribution and normal distributions and z-scores.
Probability, including union vs. intersection and independent and dependent events and Bayes' theorem.
Sampling distribution, central limit theorem and intuition behind using central limit theorem in hypothesis testing.
Hypothesis testing, including inferential statistics, significance level, type I and II errors, test statistics, and p-values. Test of proportions and chi-squar
Simple Linear Regression using manual method as well as using OLS package in python, Multiple Linear regression, and predicting using the regression model.

Who is this for?

Anyone who wants to build a career in data science but lacks the foundational skills in statistics

Data analysts who are familiar with analyzing data but want to learn concepts in statistics to be able to do rigorous analysis

Masters and research students who would like to learn statistics

Data analysts who are familiar with data analysis in excel but want to learn statistics using python

Data visualization experts who would like to explore statistics using python

What You Need to Know?

No programming experience required. You will learn the python foundations in this course.

You will need a computer with internet access to install Jupyter notebook and run python codes.

You will need to have basic math and arithmetic skills to be able to understand statistics and probability.

More details

Description
Welcome to our comprehensive course on Statistics for Data Science & Business Analytics using Python! If you're looking to gain a deep understanding of Statistics for Data Science & Business Analytics and develop the skills necessary to excel in this field, you've come to the right place. With over 10 hours of engaging video content, 75+ informative lectures and 16 thought-provoking quizzes, this course is designed to take you on a transformative learning journey. Whether you're a novice looking to build a solid foundation or an experienced professional aiming to refine your expertise, this course promises to equip you with the knowledge and tools you need to succeed.

In today's fast-paced world, staying competitive and relevant in your chosen field is more crucial than ever. This course aims to empower you with a comprehensive understanding of Statistics for Data Science & Business Analytics, covering a wide range of topics and concepts to ensure you're well-prepared for any challenges that come your way. From the fundamentals to advanced techniques, we've carefully curated the content to provide you with a holistic learning experience.

About the Instructor:
This course will be taught by Farzan Sajahan, who has an executive MBAÂ from Rotterdam School of management with over 18 years of experience in data analytics and management consulting. He has worked extensively in data analytics and operations management. He has been teaching data science for the last 4 years to over 60,000 students. He is running a management consulting firm based out of India.

What to Expect from This Course:
1. In-Depth Video Content: Our course boasts more than 10 hours of meticulously crafted video lessons. These videos are designed to make complex topics accessible and engaging. You'll have the opportunity to learn from expert in the field who will guide you through each concept, ensuring that you not only understand the theory but also its practical applications.
2. Interactive Quizzes: Learning is most effective when it's interactive. To reinforce your understanding, we've included 80 quiz questions throughout the course. These quizzes are strategically placed to test your knowledge and help you gauge your progress. Don't worry; they're not just for assessment purposesâ€”they're also fun!
3. Comprehensive Lecture Series: The 75+ lectures included in this course provide a deep dive into the subject matter. You'll explore the intricacies of Statistics for Data Science & Business Analytics, gaining insights and practical tips that are valuable for both beginners and experienced professionals. Our lecturers are passionate about the topic, and their enthusiasm will inspire and motivate you.
4. Real-World Applications: We understand that theory alone is not enough. That's why we emphasize real-world applications throughout the course. You'll learn how to put your newfound knowledge into practice, enabling you to excel in your current job or prepare for future opportunities.
5. Access to Resources: As a student in this course, you'll have access to a wealth of resources, including python notebooks and datasets. These resources are designed to enhance your learning experience and provide you with valuable references for future use.
6. Lifetime Access: Once you enroll in this course, you'll have lifetime access to all the materials. You can revisit the content whenever you need a refresher or want to explore more advanced topics. Your learning journey doesn't have an expiration date.

This course on Statistics for Data Science & Business Analytics using Python is your gateway to becoming a proficient and confident Statistics practitioner. Whether you're seeking personal growth, career advancement, or simply looking to satisfy your curiosity, we're here to guide you every step of the way. So, let's embark on this exciting journey together, unlock your potential, and discover the limitless possibilities that await you in the world of Statistics for Data Science & Business Analytics. Enroll today and let's get started!
Who this course is for:
Anyone who wants to build a career in data science but lacks the foundational skills in statistics
Data analysts who are familiar with analyzing data but want to learn concepts in statistics to be able to do rigorous analysis
Masters and research students who would like to learn statistics
Data analysts who are familiar with data analysis in excel but want to learn statistics using python
Data visualization experts who would like to explore statistics using python

User Reviews

Rating

average 0

Total votes0

Focused display

My name is Farzan Sajahan. I am a business management and data science consultant working across telecom, publishing and hospitality industries.I have over 18 years of experience in helping organizations make data driven decisions. I have a degree in electronics and communication engineering from Anna University, India and an MBA from Erasmus University, The Netherlands.And I am based out of Chennai, India.

Udemy

View courses Udemy

Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.