Course information

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 Training Course in Detroit 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 the 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 in Detroit delves into the fundamental concepts of probability and statistics, emphasizing 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 in Detroit 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 Probability and Statistics for Data Science Training in Detroit 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 analyze 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 Data Science Course in Detroit, 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 analyze data effectively, make informed decisions, and contribute meaningfully to data-driven projects within their organizations.

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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

Why choose us

Our Detroit venue

Includes..

Free Wi-Fi

To make sure you’re always connected we offer completely free and easy to access wi-fi.

Air conditioned

To keep you comfortable during your course we offer a fully air conditioned environment.

Full IT support

IT support is on hand to sort out any unforseen issues that may arise.

Video equipment

This location has full video conferencing equipment.

Detroit is the largest city in the state of Michigan, United States. It is located on the United States-Canada border and has a population of around 680,000 people. Denver’s growth is mostly to be credited to the expansion of the automobile industry as they supplied a lot of automotive support for the Allied powers during World War II. Detroit Public Schools govern 66,000 students and it is the largest district in Michigan. Detroit also has a population of charter school students at a rate of about 56,000 pupils. There are many private schools in Detroit including 110 Roman Catholic grade schools which are operated by the Archdiocese of Detroit. Detroit is home to many further education establishments including Wayne State University, University of Detroit Mercy, University of Detroit Mercy School of Law and Sacred Heart Major Seminary. Wayne State University is a national research university which focuses on medical and law majors but offers hundreds of other different academic programs. The University of Detroit Mercy is a Roman Catholic co-educational facility which is affiliated with Sisters of Mercy and Society of Jesus. It provides a wide variety of different academic degrees in a range of different subjects including dentistry, law, architecture and nursing. Sacred Heart Major Seminary is affiliated with the Pontifical University of Saint Thomas Aquinas, Angelicum in Rome. It was founded in 1919 and provides students with pontifical degrees and civil graduate or undergraduate degrees. Students are welcome to be clerical or lay. The University of Michigan was originally established in Detroit in 1817 but was then moved to Ann Arbor in 1837. Other further education facilities include the College for Creative Studies, Lewis College of Business and Marygrove College. The Michigan State University College of Osteopathic Medicine based in East Lansing also has a satellite campus based in the Detroit Medical Center. 

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Address

Detroit, Michigan

T: +1 7204454674

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 in Detroit. 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 in Detroit, 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.

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

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Team building opportunity

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Probability And Statistics For Data Science in Detroit FAQs

Statistics & Probability in Data Science focuses on foundational mathematical concepts essential in analyzing and interpreting data. It covers probability theory, distributions, hypothesis testing, and regression analysis, which are vital for making data-driven decisions and constructing predictive models in Data Science.
There are no formal prerequisites for attending this course.
This certification offers critical skills in handling and interpreting data, enabling better decision-making. It provides expertise in statistical analysis, probability theory, and data modeling, essential for solving complex problems and developing effective data-driven strategies in various industries.
This course is tailored for individuals pursuing data analysis, machine learning, or data-driven decision-making careers. Data Science, Statistics, Business Analysis, and research professionals benefit from advancing their statistical and probabilistic skills through this course.
This course focuses on core statistical concepts essential for Data Science, covering probability theory, distributions, hypothesis testing, regression analysis, and more. Delegates learn to apply statistical methods in data analysis, gaining insights into real-world scenarios, data-driven decision-making, and predictive modeling.
Yes. The Knowledge Academy offers 24/7 support for delegates before, during, and after the course. Should you encounter any difficulties accessing course materials, our customer support team is available to assist and promptly resolve any issues you may encounter.
Completing this course can lead to roles such as Data Scientist, Statistical Analyst, Business Analyst, Research Analyst, or Machine Learning Engineer. These positions require strong statistical knowledge, which is critical for interpreting and deriving insights from data in various industries.
The Knowledge Academy provides flexible self-paced training for this course. Self-paced training is beneficial for individuals who have an independent learning style and wish to study at their own pace and convenience.
The training fees for Probability and Statistics for Data Science Trainingin Detroit starts from $3195
The Knowledge Academy is the Leading global training provider for Probability and Statistics for Data Science Training.
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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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