The ‘Python for Statistical Analysis’ course delves deep into the practical applications of statistics and data science. The course also teaches how to use Python to solve common and complex statistical and Machine Learning-related projects.
This course is designed to position you for success by diving into the real-world of statistics and data science. The course is usually available for INR 2,699 on Udemy but you can click on the link and get the ‘Python for Statistical Analysis’ for INR 499.
Who all can opt for this course?
- Data scientists who seek to add statistical analysis to their skill set
- Data scientists who are interested in machine learning but want to understand more about the statistical underpinnings first
- Students who need to learn applied statistics for their research, academic assignments, or careers
|Registration Link||Apply Now!|
|Price||INR 499 (|
|Student Enrollment||53,658 students|
|Instructor||Samuel Hinton https://www.linkedin.com/in/samuelhinton|
|Topics Covered||Statistical Analysis, Python, Hypothesis Testing, Data Analysis|
|Total Student Reviews||2,564|
- Learn about Data Analysis
- Python can be used to handle simple and complex statistics and machine learning projects
- How to evaluate and visualise results while integrating graphical exploration and output
- Study hypothesis testing and effective Python test implementation
|1.||Introduction (33 minutes)||Introduction|
|Live Install and Verification|
|Live Coding Editor Comparison|
|2.||Exploring Data Analysis (02 hours 16 minutes)||Loading Data|
|Loading Data – Practical Example|
|Dataset Preparation – Practical Example|
|Dealing with Outliers – Practical Example|
|1D Distribution Overview|
|1D Histograms – Practical Example|
|1D Bee Swarm – Practical Example|
|1D Box and Violin – Practical Example|
|1D Empirical CDF and Pandas Describe – Practical Example|
|Higher Dimensional Distributions Overview|
|ND Scatter Matrix – Practical Example|
|ND Correlation – Practical Example|
|2D Histograms, Contours and KDE – Practical Example|
|ND Scatter Probability – Practical Example|
|Exploratory Data Analysis Summary|
|3.||Characterising (53 minutes)||Introduction – Why bother characterising?|
|Mean Median Mode – Practical Example|
|Widths – Practical Example|
|Skewness and Kurtosis – Practical Example|
|Percentiles – Practical Example|
|Multivariate Distributions – Practical Example|
|4.||Probability (01 hour 46 minutes)||Probability Refresher|
|Introduction to Probability Distributions|
|Probability Distributions – Practical Example|
|Probability Functions and Empirical Distributions|
|Empirical Distributions – Practical Example|
|Introduction to Sampling and the Central Limit Theorem|
|Sampling Distributions – Practical Example|
|Extra Writeup: More resources on sampling distributions|
|Central Limit Theorem – Practical Example|
|5.||Hypothesis Testing (01 hour 23 minutes)||Introduction to Hypothesis Testing|
|Motivation Loaded Die – Practical Example|
|Basic Tests Example – Asteroid Impacts|
|Introduction to Proportion Testing|
|Proportion Testing Example – Election Rigging|
|Pearsons Chi2 Test – Practical Example|
|Comparing Distributions – Kolmogorow-Smirnow and Anderson-Darling Tests|
|Extra Writeup: All the ways to do A/B testing!|
|6.||Conclusion (01 hour 45 minutes)||Conclusion|
|Extra: Significance Hunting – What not to do!|
|Extra: Introduction to Gaussian Processes|
|Extra Prac – Cosmic Impact|
|Extra Prac: Car Emission Standards|
|Extra Prac: Diagnosing Diabetes|
|Extra Prac: Numerical Uncertainty on Sales|
- Basics of Python
Carlos Andrés Campo González (5/5) : This is just what I needed and what I was looking for, great!
- Piotr Wi?ckiewicz (5/5) : This is hands-down the best udemy course I have ever done.
- Amey Kumar Samala (5/5) : I started off as a no brainer in statistical analysis, but I got a very good understanding of the statistical concepts and python packages by the end.
- Thomas Ortiz (4/5) : The instructor made very good use of Python coding techniques in the examples.
- Rafael Paranhos Gouvêa Miranda (5/5) : Great way to be introduced to Statistical Analysis using Jupyter Notebooks.
- Gaurav Shah (1/5) : The nd-scatter and outliers come of nowhere in middle impossible to understand the flow.
- Mithlesh Patel (1/5) : Went very fast, no real lofe examples, artificially created datasets only
- Malgorzata Zurek (2/5) : I will try to go through with the course as maybe it gets better later but for now, I am very disappointed.
- Vikrant Arora (2/5) : This course has been made unnecessarily complicated, the codes used are too long & complicated and instructor does not explain them in detail.
About the Author
The instructor of this course is Samuel Hinton who is a Astrophysicist, Software Engineer and Presenter. With 4.5 Instructor Rating and 4,362 Reviews on Udemy, Instructor offers 4 Courses and has taught 89,802 Students so far.
- Samuel Hinton is an astronomer, data scientist, software and robotics engineer, astrophysicist, and public speaker
- Samuel Hinton is committed to raising the level of coding proficiency in the scientific fields and imparting fundamental coding knowledge to any eager student
- Samuel Hinton has years of experience from the financial software industry to machine learning pipelines classifying objects in the night sky, as well as teaching experience in statistics, software engineering, data manipulation, computational physics, and much more
- In addition to his research work, he has led national coding courses on topics suitable for everyone from total beginners to research gurus
- Samuel Hinton is eager to share his expertise and content with a larger audience, and he believes that his straightforward style of instruction will help students learn the fundamentals more quickly and effectively while also reducing their stress levels
|Parameters||Python for Statistical Analysis||Python & Machine Learning for Financial Analysis||Python A-Z™: Python For Data Science With Real Exercises!|
|Offers||INR 499 (||INR 455 (||INR 455 (|
|Duration||8.5 hours||23 hours||11 hours|
|Instructors||Samuel Hinton||Dr. Ryan Ahmed, Ph.D., MBA||Kirill Eremenko|
|Register Here||Apply Now!||Apply Now!||Apply Now!|