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Probability And Statistics For Data Science in Manchester

Key points about this course


Duration: 2 Days *

Rating: Excellent

Language: English

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  • Gain knowledge of random variables and multivariate random variables.
  • Learn about the convergence of random processes and Markov chains.
  • Become familiarised with Bayesian statistics, hypothesis testing, and linear regression.

Available delivery methods for this course

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Onsite

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Online

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Live Virtual

Dates & Prices

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Manchester
Thu 12th Mar 2020
Places available
£1995
Manchester
Thu 14th May 2020
Places available
£1995
Manchester
Thu 9th Jul 2020
Places available
£1995
Manchester
Thu 10th Sep 2020
Places available
£1995
Manchester
Thu 12th Nov 2020
Places available
£1995

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Key points about this course


Duration: 2 Days

Support: 24/7


Course Information

Probability and Statistics for Data Science​ Training Course Overview

Probability is the most fundamental skill required to be successful in the business world. This Probability and Statistics for Data Science training course is designed to acquaint delegates with the most fundamental concepts in the field of probability. The course will equip delegates with the knowledge about probability and statistics to tackle the problems related to business and data science.

The Knowledge Academy’s Probability and Statistics for Data Science training is crafted to equip delegates with a comprehensive understanding of complicated probabilistic concepts. This course will take your career to the next level, which is of probability, Bayesian probability, conditional probability, and probability distributions.

During this 2-day course, delegates will learn about discrete and continuous random variables. The course will teach delegates how to generate multivariate random variables. In addition, delegates will gain knowledge gaussian and poisson process. Post completion of this training, delegates will become familiarised with parametric and nonparametric testing.

Probability and Statistics for Data Science​ Training Course Outline

The following modules will be covered during this Probability and Statistics for Data Science Course:

Basic Probability Theory

  • Probability Spaces
  • Conditional Probability
  • Independence

Random Variables

  • Definition
  • Discrete Random Variables 
  • Continuous Random Variables
  • Conditioning on an Event
  • Functions of Random Variables
  • Generating Random Variables
  • Proofs

Multivariate Random Variables

  • Discrete Random Variables
  • Continuous Random Variables
  • Joint distributions of Discrete and Continuous Variables
  • Independence
  • Functions of Several Random Variables
  • Creating Multivariate Random Variables
  • Rejection Sampling

Expectation

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

Random Processes

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

The convergence of Random Processes

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

Markov Chains

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

Descriptive Statistics

  • Histogram
  • Sample Mean and Variance
  • Order Statistics
  • Sample Covariance
  • Sample Covariance Matrix

Frequentist Statistics

  • Independent Identically-Distributed Sampling
  • Mean Square Error
  • Consistency
  • Confidence Intervals
  • Nonparametric Model Estimation
  • Parametric Model Estimation
  • Proofs

Bayesian Statistics

  • Bayesian Parametric Models
  • Conjugate Prior
  • Bayesian Estimators

Hypothesis Testing

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

Linear Regression

  • Linear Models
  • Least-Squares Estimation
  • Overfitting

Prerequisites

There are no formal prerequisites for attending this course.

Audience

Anyone interested in learning how to apply probability and statistics to data science can attend this course.

Please arrive at the venue at 8:45am.
There are no formal prerequisites for attending this course.
Anyone interested in learning how to apply probability and statistics to data science can attend this course.
We are able to provide support via phone & email prior to attending, during and after the course.
Delegate pack consisting of course notes and exercises, Manual, Experienced Instructor, and Refreshments
This course is 2 days.
Once your booking has been placed and confirmed, you will receive an email which contains your course location, course overview, pre-course reading material (if required), course agenda and payment receipts
The price for Probability and Statistics for Data Science Training certification in Manchester starts from £1995
The Knowledge Academy is the Leading global training provider in the world for Probability and Statistics for Data Science Training.
  • Delegate pack consisting of course notes and exercises
  • Manual
  • Experienced Instructor

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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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Various delivery methods

Flexible delivery methods are available depending on your learning style.

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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"

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"...the trainer for this course was excellent. I would definitely recommend (and already have) this course to others."

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