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Statistics & Probability for Data Science & Machine Learning - Level 7 (QLS Endorsed)

QLS Endorsed + CPD QS Accredited - Dual Certification | Instant Access | 24/7 Tutor Support


Kingston Open College

Summary

Price
£15 inc VAT
Study method
Online
Duration
600 hours · Self-paced
Access to content
12 months
Qualification
No formal qualification
CPD
180 CPD hours / points
Achievement
Certificates
  • Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Le - £75
Additional info
  • Exam(s) / assessment(s) not included in price, and must be purchased separately
  • Tutor is available to students
  • TOTUM card available but not included in price What's this?

1 student purchased this course

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Overview

The most critical aspect of data science and machine learning is a knowledge of probability and statistics. Statistics provides us with the tools to gather, process, and understand data, while probability theory aids in quantifying uncertainty and interpreting incomplete information. Professionals can build robust forecasting frameworks and gain substantial insight from information thanks to the interaction between these disciplines. The course "Statistics & Probability for Data Science & Machine Learning" provides students with the fundamental skills and knowledge required to excel in data-driven decision-making by thoroughly examining this connection.

Our QLS-approved “Statistics & Probability for Data Science & Machine Learning” course starts with the fundamentals. It moves quickly into descriptive statistics, which helps students effectively summarise and analyse data. Subsequently, it explores probability distributions and theory, thoroughly comprehending uncertainty and its measurement. While regressions give students insights into predictive modelling, hypothesis testing allows them to make meaningful inferences from data. Moving on to the following portion, the course discusses sophisticated machine learning algorithms and regression techniques essential for data-driven insights. Variance analysis methods are extended by ANOVA (Analysis of Variance). The course ends with a thorough wrap-up that reinforces the learning process.

What’s more? The quality of our first-class course is uncompromising for both you and us. You will be taught the richest materials from this exquisite Statistics & Probability for Data Science & Machine Learning course, enabling you to open up a vast world of opportunities to grasp and gain success. For the price point, this course is an absolute steal! It’s an investment you want to take advantage of!

Take on a life-changing educational journey to understand the probability and statistics fundamentals underpinning data science and machine learning. Come along as we use predictive analytics and well-informed decision-making to unleash the potential of data! To increase your comprehension, you can just enroll right away.

Learning Outcome of the “Statistics & Probability for Data Science & Machine Learning” course:

  • Utilise descriptive statistics to accurately and succinctly summarise and analyse various datasets
  • Comprehend uncertainty, make wise decisions, and analyse different probability distributions
  • Get practical conclusions from experimental data and apply hypothesis-testing techniques
  • Use regression modelling approaches to get meaningful data analysis and predictive modelling
  • For reliable predictive modelling, use sophisticated machine learning and regression methods
  • Use ANOVA methods to analyse variance and inferential statistics efficiently

Why Learn Statistics & Probability for Data Science & Machine Learning with us:

As one of the leading e-learning service providers globally, we strive to provide all our learners with the best e-learning experience possible that can make a real difference in their career progression.

Our Service for Statistics & Probability for Data Science & Machine Learning:

  • Intensive Study Notes
  • Tutor Support
  • Customer Support
  • Teaching Assistant Assignment Help
  • QLS Endorsed Teaching Assistant Certificate
  • 24/7 Learning Portal Access
  • Widely Compatible Teaching Assistant Study Materials
  • 14 Days Refund Guarantee

Achievement

CPD

180 CPD hours / points
Accredited by CPD Quality Standards

Course media

Description

Statistics & Probability for Data Science & Machine Learning

  • Section 01: Let’s get started
  • Section 02: Descriptive statistics
  • Section 03: Distributions
  • Section 04: Probability theory
  • Section 05: Hypothesis testing
  • Section 06: Regressions
  • Section 07: Advanced regression & machine learning algorithms
  • Section 08: ANOVA (Analysis of Variance)
  • Section 09: Wrap up

Assessment & Certification

Students must finish and turn in a thorough assignment covering all topics in our curriculum. Our expert tutor will review the assignment to ensure it meets Quality Learning Systems (QLS) standards. Once the assessment is successful and passes a quality check, students will be awarded a certificate for completing the Statistics & Probability for Data Science & Machine Learning Course.

Endorsed Certificate of Achievement from the Quality Licence Scheme.

After the course, participants will receive an endorsed certificate as proof of successful completion. The learner may request a certificate if they complete all course assessments.

Endorsement:

After the course, participants will receive an endorsed certificate as proof of successful completion. The learner may request a certificate if they complete all course assessments.

Who is this course for?

The “Statistics & Probability for Data Science & Machine Learning” course is designed to be accessible to all. However, the following learners can take the best out of it:

  • Those who analyse data and want to improve their statistical and probability knowledge
  • The machine learning engineer whose goal is to improve the fundamental knowledge of statistics needed for modelling
  • Data scientists hope to improve predictive modelling using sophisticated ML and regression algorithms
  • Business analysts hope to use statistical hypothesis testing to enhance decision-making
  • Inferential statistics and ANOVA are widely used by researchers in data analysis
  • Professionals or students making the shift to a data-centric career path

Requirements

No specific requirements exist for enrolling in the “Statistics & Probability for Data Science & Machine Learning”course. Therefore, learners do not need previous qualifications to sign up for this course.

Career path

The “Statistics & Probability for Data Science & Machine Learning” skills are required in many careers in the UK, including:

  • Data Analyst: £25,000 – £50,000 per year
  • Data Scientist: £35,000 – £80,000 per year
  • Machine Learning Engineer: £40,000 – £90,000 per year
  • Statistician: £30,000 – £60,000 per year
  • Research Analyst (with statistical skills): £25,000 – £50,000 per year

Questions and answers

Currently there are no Q&As for this course. Be the first to ask a question.

Certificates

Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Le

Hard copy certificate - £75

Reviews

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FAQs

Study method describes the format in which the course will be delivered. At Reed Courses, courses are delivered in a number of ways, including online courses, where the course content can be accessed online remotely, and classroom courses, where courses are delivered in person at a classroom venue.

CPD stands for Continuing Professional Development. If you work in certain professions or for certain companies, your employer may require you to complete a number of CPD hours or points, per year. You can find a range of CPD courses on Reed Courses, many of which can be completed online.

A regulated qualification is delivered by a learning institution which is regulated by a government body. In England, the government body which regulates courses is Ofqual. Ofqual regulated qualifications sit on the Regulated Qualifications Framework (RQF), which can help students understand how different qualifications in different fields compare to each other. The framework also helps students to understand what qualifications they need to progress towards a higher learning goal, such as a university degree or equivalent higher education award.

An endorsed course is a skills based course which has been checked over and approved by an independent awarding body. Endorsed courses are not regulated so do not result in a qualification - however, the student can usually purchase a certificate showing the awarding body's logo if they wish. Certain awarding bodies - such as Quality Licence Scheme and TQUK - have developed endorsement schemes as a way to help students select the best skills based courses for them.