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 New York 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 New York 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 New York 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 New York 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 New York, 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 New York 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.

New York City is the biggest city in the United States. It is the most populous urban agglomerations in the world. New York is often described as the cultural and financial capital of the world. Education in the USA is provided by both public and private schools, and is mandatory until the age of 16.  Pupils conducting their schooling within the USA start off at preschool, followed by elementary school, then middle school, before finishing at high school.  At age 18, US citizens are able to engage in higher education.  Higher education in the USA normally comes in the form of a college, undergraduate school, or a community college – that latter of which doesn’t normally cost anything to attend.  Candidates participating in a course at a college will gain credits towards a bachelor’s degree, whilst candidates participating a course at a community college will be earning credits in order to achieve an associate’s degree. The public school system is run by the New York City Public School board. It is the biggest school system in the United States. They serve approximately 1.1 million pupils in 1,700 schools. There are nine special schools for those who are academically or artistically gifted. There are approximately 900 additional privately-run secular and religious schools in the city. There are roughly 600,000 students in New York that are enrolled in one of the 120 higher education institutions. There are a number of notable universities in the City of New York. These include: Columbia University, New York University and the New York Institute of Technology. Columbia is the highest ranked New York University in the world rankings, coming in at number 22. It is a private Ivy League research university that has twenty school including Columbia College, the School of Engineering and Applied Science, and the School of General Studies. New York is also home to a number of specialist art schools such as the world renowned Juilliard School that specialises in the performing arts. At The Knowledge Academy we offer over 50,000 classroom based training courses in the United States, including popular locations such as New York.

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Address

NYC Seminar and Conference Center
71 West 23rd Street
Suite 515
New York
NY 10010

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

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Team building opportunity

Our 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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Probability And Statistics For Data Science in New York 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 New York starts from $3195
The Knowledge Academy is the Leading global training provider for Probability and Statistics for Data Science Training.
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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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