Probability and Statistics in Data Science using Python Training

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Using Python, learn statistical and probabilistic approaches to understand and gain insights from data.

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What is Probability and Statistics in Data Science using Python Training about?

In this course, part of the Data Science MicroMasters program, you will learn the foundations of probability and statistics. You will learn both the mathematical theory, and get hands-on experience in applying this theory to actual data using Jupyter notebooks. Concepts covered included: random variables, dependence, correlation, regression, PCA, entropy, and MDL.

What are the objectives of Probability and Statistics in Data Science using Python Training ?

The mathematical foundations for machine learning
Statistics literacy: understand the meaning of statements such as "at a 99% confidence level"

Who is Probability and Statistics in Data Science using Python Training for?

People interested in a Business Intelligence career
Business analysts
Business executives
Individuals who are passionate about numbers and quant analysis
Anyone who wants to learn the subtleties of Probability and how it is used in the business world
People who want to start learning probability
People who want to learn the fundamentals of probability
People who wish to extract insights from summarised statistics to understand academic papers

What are the prerequisites for Probability and Statistics in Data Science using Python Training?

The previous course in the MicroMasters program: DSE200x
Undergraduate level education in – Multivariate calculus, Linear Algebra

Available Training Modes

Live Online Training

80 Hours

Self-Paced Training

80 Hours

Course Outline Expand All

Expand All

Module – 1: Introduction to Probability and Statistics

Module – 2: Sets

Module – 3: Counting

Module – 4: Combinatorics

Module – 5: Probability Introduction

Module – 6: Conditional Probability

Module – 7: Random Variables, Expectation, and Variance

Module – 8: Discrete Distribution Families

Module – 9: Continuous Distribution Families

Module – 10: Inequalities and Limit Theorems

Module – 11: Statistics, Parameter Estimation, and Confidence Interval

Module – 12: Regression and PCA

Module – 13: Hypothesis Testing

Who is the instructor for this training?

The trainer for this Probability and Statistics in Data Science using Python Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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