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Probability and Statistics for Data Science Training is part of our Black Friday sale. Lock in 59% off now, choose online, classroom or onsite training, and schedule your course any time through 2027. Group bookings save up to 60%.

FROM NZD2,795 NZD6,895 SAVE NZD4,100

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Probability and Statistics for Data Science Training Overview

Course syllabus

Who it’s for

What’s included

FAQs

Probability and Statistics for Data Science​ Training Course Outline

Day 1: Probability and Random Variables

Module 1: Basic Probability Theory
  • Probability Spaces
  • Conditional Probability
  • Independence
Module 2: Random Variables
  • Random Variables Intro
  • Discrete Random Variables
  • Continuous Random Variables
  • Conditioning on Events
  • Functions of Random Variables
  • Generating Random Variables
Module 3: Multivariate Random Variables
  • Introduction
  • Discrete & Continuous Multivariate Variables
  • Joint Distributions
  • Independence
  • Functions of Several Variables
  • Generating Multivariate Variables & Rejection Sampling
Module 4: Expectation
  • Expectation Operator, Mean and Variance
  • Covariance, Conditional Expectation
Module 5: Random Processes
  • Intro, Mean, and Autocovariance Functions
  • IID
  • Gaussian Process
  • Poisson Process
  • Random Walk

Day 2: Statistics and Applications (8 hours total)

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 and Basic Concepts
  • Recurrence
  • Periodicity
  • Convergence
  • Introduction to Markov-Chain Monte Carlo (MCMC)
Module 8: Descriptive Statistics
  • What are Descriptive Statistics?
  • Examples and Types of Descriptive Statistics
Module 9: Frequentist Statistics
  • Mean Square Error
  • Consistency
  • Confidence Intervals
  • Parametric vs Nonparametric Model Estimation
  • Maximum Likelihood Estimation (MLE)
Module 10: Bayesian Statistics
  • Bayesian Parametric Models
  • Conjugate Priors
  • Bayesian Estimators
Module 11: Hypothesis Testing
  • Hypothesis-Testing Framework
  • Parametric Testing
  • Nonparametric Testing: The Permutation Test
  • Multiple Testing Correction
Module 12: Linear Regression
  • Introduction to Linear Regression
  • Linear Models & Applications
  • Least-Squares Estimation
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Who Should Attend this Probability and Statistics for Data Science Training?

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

There are no formal prerequisites for this course.

Probability and Statistics for Data Science Training Course Overview

Probability and Statistics Training introduces delegates to the core concepts that underpin data-driven decision-making. It explains how uncertainty, variability, and data patterns are measured and interpreted, forming the foundation for meaningful analysis in Data Science.

This training supports professionals working with data in building analytical confidence. It develops the ability to quantify uncertainty, recognise trends, and draw accurate conclusions, enabling informed decisions across analytical and business-focused roles.

This 2-Day course offered by The Knowledge Academy enables delegates to apply probability and statistics with confidence. Through focused learning, delegates gain the skills to work with distributions, hypothesis testing, and regression, supporting practical, evidence-based decisions.

Probability and Statistics for Data Science Training 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 Data Science Training, 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?

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

Looking for Probability and Statistics for Data Science Training in-house or onsite training Hamilton City. We specialise in corporate group training and bulk bookings for organisations of all sizes. Our trainers deliver tailored sessions at your premises, online, or hybrid, with best price guarantee, group discounts and flexible scheduling.

Approved supplier to 53,550 organisations

The Knowledge Academy is an approved training supplier to 53,550 organisations across the UK, Europe, North America and Australia, so most buyers can book through their existing purchasing process with no new supplier setup.

Our Hamilton City 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.

Hamilton is the most populous city situated in the North Island of New Zealand. Hamilton homes around 154,000 people making it the fourth most populous country in New Zealand. Education and Research play a huge part in Hamilton’s economy. The city is home to around 40,000 higher education students and 1,000 PhD qualified scientists. There are three main universities in Hamilton, the University of Waikato, Waikato Institute of Technology and Te Wananga o Aotearoa. As well as the higher education, Hamilton is also home to a number of Kura Kaupapa Maori schools which offer education in the Maori language. The University of Waikato is a comprehensive university in Hamilton. The University was established in 1964 and was the first university in New Zealand be designed from scratch. The university houses around 10,000 students who can study a variety of subjects, such as Arts, Social Sciences, Computing and Mathematical Science, Education, Law and Engineering. The University of Waikato produced many notable alumni such as Nathan Cohen who is a two time world champion and Olympic champion in rowing. The Waikato Institute of Technology has around 20,000 students. The institute offers students 10 degree programs, 35 diplomas and 12 postgraduate qualifications. The Waikato Institute of Technology has three campuses in Hamilton, which all specialise in various areas, such as engineering, science, technology, sport, health and tourism. The institute works closely with employers to ensure students are work ready when they leave the institution. Te Wananga o Aoteraroa is a specialised university that focus of giving a positive learning experience to students who have previously had negative experiences with the education system. The University if a Maori led institute and focus strongly on Maori traditions and values. Te Wananga o Aotearoa is currently one of the largest tertiary education providers in New Zealand. The Institute caters to around 35,000 students each year and has more than 100 sites. Te Wananga o Aotearoa was established in 1983 to provide education for students whose needs are not being met in mainstream education. 

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Ways to take Probability and Statistics for Data Science Training in Hamilton City

Live Online

The same live course from home, with a live instructor and other delegates. Mirrors the classroom schedule.

Best for: starting soon, without travel.

2 days · next Thu 19 Nov 2026

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Online Self-Paced

Study 24/7 on your own schedule through our learning platform, with progress tracking.

Best for: fitting study around work.

90 days of access

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Onsite

We bring the course to your team, at your premises, online or hybrid, on dates that suit you.

Best for: groups and bulk bookings.

Tailored to your team

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Package deals for Probability and Statistics for Data Science Training in Hamilton City

Our training experts have compiled a range of course packages on a variety of categories in Probability and Statistics for Data Science Training, to boost your career. The packages consist of the best possible qualifications with Probability and Statistics for Data Science Training, and allows you to purchase multiple courses at a discounted rate.

Probability And Statistics For Data Science in Hamilton City FAQs

What is the use of Probability and Statistics in Data Science?

Probability and statistics help data scientists model uncertainty, analyse patterns, draw conclusions, and make informed decisions. They underpin predictive analytics, machine learning algorithms, data interpretation, and experimentation across various real-world business, scientific, and technological applications.

What are the pre-requisites of taking up Probability and Statistics for Data Science Course?

There are no formal prerequisites for this course.

Who should attend this course?

This course suits Data Analysts, Aspiring Data Scientists, Business Analysts, Researchers, Students, and Professionals interested in data-driven decision-making, machine learning, or statistical modelling. It’s ideal for building or reinforcing analytical and quantitative reasoning skills.

What is the Markov Chain?

A Markov Chain is a stochastic model describing a sequence of possible events where the probability of each event depends only on the state attained in the previous event, commonly used in predictive modelling and decision analysis.

What is a random variable?

A random variable represents a numerical outcome of a random phenomenon. It can be discrete or continuous and is used to quantify and analyse data distributions, probabilities, and expectations in statistical models.

What is the duration of this course?

This course takes 2-Day to complete during which delegates participate in intensive learning sessions that cover various course topics.

What is hypothesis testing?

Hypothesis testing is a statistical method used to determine whether there is enough evidence to support a specific claim about a population parameter, based on sample data, using tests like t-tests or chi-square.

What will I learn in this Probability and Statistics for Data Science Training Course?

You will learn probability theory, statistical distributions, sampling, hypothesis testing, regression, Markov Chains, random variables, and data interpretation techniques essential for data science, machine learning, and evidence-based business decision-making.

What is the demand for Probabaility and Statistics for Data Science Courses in the future?

Demand will remain high, as data-driven decision-making grows across industries. Core statistical knowledge is foundational for roles in AI, machine learning, and business analytics, making this training increasingly relevant and valuable.

How popular is the Probability and Statistics for Data Science Certification in Hamilton City?

The certification is gaining popularity in Hamilton City due to rising demand for data professionals. Employers across sectors value candidates with strong statistical foundations for roles involving data analytics and predictive modelling.

What job opportunities will one get on completing Probability and Statistics for Data Science Training?

Roles include Data Analyst, Statistician, Business Analyst, Data Scientist, Machine Learning Engineer, and Research Analyst. This training strengthens analytical credentials and improves employability in industries driven by data and evidence-based decision-making.

What topics are covered in the course?

The course covers probability theory, random variables, expectation, random processes, convergence, Markov chains, descriptive statistics, frequentist and Bayesian methods, hypothesis testing, Monte Carlo simulations, and linear regression, providing a comprehensive foundation in statistical methods for Data Science applications.

What is the cost/training fees for Probability and Statistics for Data Science Training in Hamilton City?

The training fees for Probability and Statistics for Data Science Training in Hamilton City starts from NZD6895

Which is the best training institute/provider of Probability and Statistics for Data Science Training in Hamilton City?

The Knowledge Academy is one of the Leading global training provider for Probability and Statistics for Data Science Training.

What are the best Data Science Courses courses in Hamilton City?

Please see our Data Science Courses courses available in Hamilton City

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