Probability and Statistics for Data Science Training Overview

Probability and Statistics for Data Science​ Training Course Outline

Module 1: Basic Probability Theory

  • Probability Spaces
  • Conditional Probability
  • Independence

Module 2: Random Variables

  • What are Random Variables?
  • Discrete Random Variables
  • Continuous Random Variables
  • Conditioning on an Event
  • Functions of Random Variables
  • Generating Random Variables

Module 3: Multivariate Random Variables

  • Introduction to Multivariate Random Variables
  • Discrete Random Variables
  • Continuous Random Variables
  • Joint Distributions of Discrete and Continuous Variables
  • Independence
  • Functions of Several Random Variables
  • Generating Multivariate Random Variables
  • Rejection Sampling

Module 4: Expectation

  • Expectation Operator
  • Mean and Variance
  • Covariance
  • Conditional Expectation

Module 5: Random Processes

  • Introduction to Random Process
  • Mean and Autocovariance Functions
  • Independent Identically-Distributed Sequences Gaussian Process
  • Poisson Process
  • Random Walk

Module 6: Convergence of Random Processes

  • Types of Convergence
  • Law of Large Numbers
  • Central Limit Theorem
  • Monte Carlo Simulation

Module 7: Markov Chains

  • Markov Property
  • Time-Homogeneous Discrete-Time Markov Chains
  • Recurrence
  • Periodicity
  • Convergence
  • Markov-Chain Monte Carlo

Module 8: Descriptive Statistics

  • What is Descriptive Statistics?
  • Examples of Descriptive Statistics
  • Types of Descriptive Statistics

Module 9: Frequentist Statistics

  • Mean Square Error
  • Consistency
  • Confidence Intervals
  • Nonparametric Model Estimation
  • Parametric Model Estimation
  • Maximum Likelihood

Module 10: Bayesian Statistics

  • Bayesian Parametric Models
  • Conjugate Prior
  • Bayesian Estimators

Module 11: Hypothesis Testing

  • Hypothesis-Testing Framework
  • Parametric Testing
  • Nonparametric Testing: The Permutation Test
  • Multiple Testing

Module 12: Linear Regression

  • Introduction to Linear Regression
  • Linear Models
  • Least-Squares Estimation

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Who should attend this Probability and Statistics for Data Science Training Course?

This Probability and Statistics for Data Science Course is designed to provide foundational and practical knowledge in Probability and Statistics, which are crucial for Data Science, Machine Learning, and Data Analysis. The following are some professionals who will benefit from attending this Course:

  • Data Scientists
  • Machine Learning Engineers
  • Data Analysts
  • Business Analysts
  • Product Managers
  • Quantitative Analysts
  • Statisticians

Prerequisites of the Probability and Statistics for Data Science Training Course

There are no prerequisites for Probability and Statistics for Data Science Course.

Probability and Statistics for Data Science Training Course Overview

Probability and statistics form the foundational pillars of data science, providing the necessary tools for understanding uncertainty, variability, and making informed decisions based on data. This training course delves into the fundamental concepts of probability and statistics, emphasising their crucial role in the field of data science. Delegates will explore how these concepts contribute to the extraction of meaningful insights and patterns from data.

Understanding probability and statistics is essential for professionals in the data science domain. Data scientists, analysts, and decision-makers rely on these principles to draw accurate conclusions and predictions from data. Mastery of probability allows for the quantification of uncertainty, while statistics enables the analysis of data patterns and trends.

This 2-day training will empower the delegates with the skills to apply probability and statistics in practical data science scenarios. They will learn key concepts such as probability distributions, hypothesis testing, and regression analysis. The course provides a comprehensive understanding of statistical methods, enabling professionals to make informed decisions and predictions based on data

Course Objectives

  • To represent and analyse uncertain phenomena using a framework
  • To quantify the outcome of the experiment as belonging to a specific event
  • To assign probabilities to each occurrence of interest and an experiment
  • To become accustomed to Markov chains and different statistical types
  • To generate samples from the appropriate conditional distribution
  • To evaluate the occurrence of a particular event that influences another event

Upon completion of this course, the delegates will possess a strong foundation in probability and statistics for data science. They will be equipped with the tools and techniques needed to analyse data effectively, make informed decisions, and contribute meaningfully to data-driven projects within their organisations.

 

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What’s included in this Probability and Statistics for Data Science Training Course?

  • World-Class Training Sessions from Experienced Instructors 
  • Probability and Statistics for Data Science Certificate 
  • Digital Delegate Pack

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Why choose us

Ways to take this course

Experience live, interactive learning from home with The Knowledge Academy's Online Instructor-led Probability and Statistics for Data Science Training. Engage directly with expert instructors, mirroring the classroom schedule for a comprehensive learning journey. Enjoy the convenience of virtual learning without compromising on the quality of interaction.

Unlock your potential with The Knowledge Academy's Probability and Statistics for Data Science Training, accessible anytime, anywhere on any device. Enjoy 90 days of online course access, extendable upon request, and benefit from the support of our expert trainers. Elevate your skills at your own pace with our Online Self-paced sessions.

Experience the most sought-after learning style with The Knowledge Academy's Probability and Statistics for Data Science Training. Available in 490+ locations across 190+ countries, our hand-picked Classroom venues offer an invaluable human touch. Immerse yourself in a comprehensive, interactive experience with our expert-led Probability and Statistics for Data Science Training sessions.

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Highly experienced trainers

Boost your skills with our expert trainers, boasting 10+ years of real-world experience, ensuring an engaging and informative training experience

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State of the art training venues

We only use the highest standard of learning facilities to make sure your experience is as comfortable and distraction-free as possible

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Small class sizes

Our Classroom courses with limited class sizes foster discussions and provide a personalised, interactive learning environment

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Great value for money

Achieve certification without breaking the bank. Find a lower price elsewhere? We'll match it to guarantee you the best value

Streamline large-scale training requirements with The Knowledge Academy’s In-house/Onsite Probability and Statistics for Data Science Training at your business premises. Experience expert-led classroom learning from the comfort of your workplace and engage professional development.

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Tailored learning experience

Leverage benefits offered from a certification that fits your unique business or project needs

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Maximise your training budget

Cut unnecessary costs and focus your entire budget on what really matters, the training.

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Team building opportunity

Our Probability and Statistics for Data Science Training offers a unique chance for your team to bond and engage in discussions, enriching the learning experience beyond traditional classroom settings

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Monitor employees progress

The course know-how will help you track and evaluate your employees' progression and performance with relative ease

What our customers are saying

Probability and Statistics for Data Science Training FAQs

Probability is used to predict the outcome of an event about to occur, and statistics is helpful to estimate the values for further analysis, which depends on probability theory. Both probability and statistics rely on the data.
There are no formal prerequisites for attending this Probability and Statistics for Data Science Training course.
This training is suitable for anyone who wants to learn how to apply probability and statistics in Data Science.
Markov Chain is the mathematical function used to model random processes in discrete spaces that satisfy the Markov property. Markov property is satisfied when a current state can predict a future state.
A random variable is a numeric value associated with a probability that depends on the random process. It can be discrete or continuous.
This course is 2 days.
Hypothesis testing is the statistical testing of the predictions made by Researchers and Data Scientists regarding the natural world, whether these are true or not.
In this Probability and Statistics for Data Science Training course, you will learn how to apply probability theory and statistics in data science for prediction and estimations, hypothesis testing, Markov Chain, linear regression, multivariate random variables, expectations, random processes, descriptive statistics, and other related concepts.
The training fees for Probability and Statistics for Data Science Training certification in Philippines starts from $3195
The Knowledge Academy is the Leading global training provider for Probability and Statistics for Data Science Training.
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You won't find better value in the marketplace. If you do find a lower price, we will beat it.

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Many delivery methods

Flexible delivery methods are available depending on your learning style.

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High quality resources

Resources are included for a comprehensive learning experience.

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"Really good course and well organised. Trainer was great with a sense of humour - his experience allowed a free flowing course, structured to help you gain as much information & relevant experience whilst helping prepare you for the exam"

Joshua Davies, Thames Water

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