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Level 7 Advanced Diploma in Data Science & Machine Learning with Python cover image

Level 7 Advanced Diploma in Data Science & Machine Learning with Python
Janets

Level 7 QLS Endorsed | Free QLS Hardcopy Certificate | Free Exam | 180 CPD Points | Lifetime Access | 24x7 Tutor Support

Summary

Price
£125 inc VAT
Or £41.67/mo. for 3 months...
Study method
Online
Course format
Video
Duration
600 hours · Self-paced
Access to content
Lifetime access
Qualification
No formal qualification
CPD
180 CPD hours / points
CPD What's this?
Achievement
Endorsed by The Quality Licence Scheme
Certificates
  • CPD Accredited PDF Certificate - Free
  • QLS Endorsed Hardcopy Certificate - Free
  • CPD Accredited Hard Copy Certificate - £15.99
Additional info
  • Exam(s) / assessment(s) is included in price
  • Tutor is available to students

Overview

Data is the new currency of innovation — driving insights, shaping decisions, and powering intelligent systems across industries. The Level 7 Advanced Diploma in Data Science & Machine Learning with Python is your gateway to mastering this dynamic landscape. More than just a course, it’s a pathway to fluency in the language of the future. From writing your first Python script to developing sophisticated machine learning models, this programme equips you with the skills to transform data into meaningful, actionable outcomes. It's where curiosity meets cutting-edge technology, and where your journey into the data-driven world truly begins.

Throughout the course, you’ll build a strong foundation in Python programming before progressing to the essential pillars of data science. You'll dive into data collection, analysis, and visualisation, and advance through machine learning techniques including regression, classification, clustering, and neural networks. Key topics like model evaluation, data preparation, and algorithm optimisation ensure that your knowledge is both deep and versatile — ready for real-world challenges.

Take the next step into one of the UK's fastest-growing and most exciting fields. Enrol in the Level 7 Advanced Diploma in Data Science & Machine Learning with Python today and future-proof your career!

Learning Outcomes

  • Understand foundational machine learning concepts and applications.
  • Master Python basics and apply advanced data analysis libraries.
  • Interpret and visualise datasets for deeper insights.
  • Evaluate machine learning algorithms using various metrics.
  • Optimise model performance through ensembles and parameter tuning.
  • Finalise and deploy models for real-time predictions.

Achievement

Certificates

CPD

180 CPD hours / points
Accredited by CPD Quality Standards

Course media

Description

Dive deep into the world of data science and machine learning with this comprehensive Advanced Diploma in Data Science & Machine Learning with Python at QLS Level 7 course. Throughout the course, learners will be immersed in the foundational concepts of machine learning, coupled with hands-on Python programming exercises.

Essential libraries such as NumPy, Pandas, and Matplotlib are explored to enable robust data analysis. Participants will also journey through a myriad of algorithm evaluation techniques, refining their ability to select and optimise the most effective models. By the end of the course, learners will be adept at finalising and deploying models to make real-time predictions.

Course Curriculum:

  • Course Overview & Table of Contents
  • Introduction to Machine Learning - Part 1 - Concepts, Definitions and Types
  • Introduction to Machine Learning - Part 2 - Classifications and Applications
  • System and Environment Preparation - Part 1
  • System and Environment Preparation - Part 2
  • Learn Basics of Python - Assignment
  • Learn Basics of Python - Assignment
  • Learn Basics of Python - Functions
  • Learn Basics of NumPy - NumPy Array
  • Learn Basics of NumPy - NumPy Data
  • Learn Basics of NumPy - NumPy Arithmetic
  • Learn Basics of Matplotlib
  • Learn Basics of Pandas - Part 1
  • Learn Basics of Pandas - Part 2
  • Explaining Correlation
  • Explaining Skewness - Gaussian and Normal Curve
  • Using Histograms
  • Using Density Plots
  • Box and Whisker Plots
  • Multivariate Visualization - Correlation Plots
  • Multivariate Visualization - Scatter Plots
  • Feature Selection - Introduction
  • Feature Selection - Uni-variate Part 1 - Chi-Squared Test
  • Feature Selection - Uni-variate Part 2 - Chi-Squared Test
  • Feature Selection - Recursive Feature Elimination
  • Feature Selection - Principal Component Analysis (PCA)
  • Feature Selection - Feature Importance
  • Refresher Session - The Mechanism of Re-sampling, Training and Testing
  • Algorithm Evaluation Techniques - Introduction
  • Algorithm Evaluation Techniques - Train and Test Set
  • Algorithm Evaluation Techniques - K-Fold Cross Validation
  • Algorithm Evaluation Techniques - Leave One Out Cross Validation
  • Algorithm Evaluation Techniques - Repeated Random Test-Train Splits
  • Algorithm Evaluation Metrics - Introduction
  • Algorithm Evaluation Metrics - Classification Accuracy
  • Algorithm Evaluation Metrics - Log Loss
  • Algorithm Evaluation Metrics - Area Under ROC Curve
  • Algorithm Evaluation Metrics - Confusion Matrix
  • Algorithm Evaluation Metrics - Classification Report
  • Algorithm Evaluation Metrics - Mean Absolute Error
  • Algorithm Evaluation Metrics - Mean Absolute Error
  • Algorithm Evaluation Metrics - Mean Square Error
  • Algorithm Evaluation Metrics - R Squared
  • Classification Algorithm Spot Check - Logistic Regression
  • Classification Algorithm Spot Check - Linear Discriminant Analysis
  • Classification Algorithm Spot Check - K-Nearest Neighbors
  • Classification Algorithm Spot Check - Naive Bayes
  • Classification Algorithm Spot Check - CART
  • Classification Algorithm Spot Check - Support Vector Machines
  • Regression Algorithm Spot Check - Linear Regression
  • Regression Algorithm Spot Check - Ridge Regression
  • Regression Algorithm Spot Check - Lasso Linear Regression
  • Regression Algorithm Spot Check - Elastic Net Regression
  • Regression Algorithm Spot Check - K-Nearest Neighbors
  • Regression Algorithm Spot Check - CART
  • Regression Algorithm Spot Check - Support Vector Machines (SVM)
  • Compare Algorithms - Part 1: Choosing the Best Machine Learning Model
  • Compare Algorithms - Part 2: Choosing the Best Machine Learning Model
  • Performance Improvement: Ensembles - Voting
  • Performance Improvement: Ensembles - Bagging
  • Performance Improvement: Ensembles - Boosting
  • Performance Improvement: Parameter Tuning using Grid Search
  • Performance Improvement: Parameter Tuning using Random Search
  • Export, Save and Load Machine Learning Models: Pickle
  • Export, Save and Load Machine Learning Models: Joblib
  • Finalizing a Model - Introduction and Steps
  • Finalizing a Classification Model
  • Finalizing Multi-Class
  • Finalizing a Regression Model - The Boston Housing Price
  • Real-time Predictions: Using the Pima Indian Diabetes Classification Model
  • Real-time Predictions: Using Iris Flowers Multi-Class Classification
  • Real-time Predictions: Using the Boston Housing Regression Model
  • Resources

Method of Assessment

To successfully complete the course, students will have to take an automated multiple-choice exam. This exam will be online, and you will need to score 60% or above to pass the course. After successfully passing the course exam, you will be able to apply for a certificate as proof of your expertise.

What You Get Out Of Studying With Janets

  • Free PDF certificate upon successful completion of the course
  • Lifetime access to course materials
  • Instant assessment results
  • Full tutor support is available from Monday to Friday
  • Study the course at your own pace
  • Accessible, informative modules taught by expert instructors
  • Get 24/7 help or advice from our email and live chat teams with the course
  • Study at your own time through your computer, tablet or mobile device
  • Improve your chance of gaining valuable skills by completing the course

Enrol in the Advanced Diploma at QLS Level 7 course to find out more about the topic and get one step closer to reaching your desired success!!

Who is this course for?

This course is designed for:

  • Aspiring professionals seeking a comprehensive education.
  • Professionals in IT and analytics aiming to broaden their knowledge in Python and machine learning.
  • Academics and researchers interested in applying methodologies in their work.
  • Business analysts wanting to leverage for more insightful interpretation.
  • Technology enthusiasts eager to explore the potential of machine learning and Python in solving complex problems.

Requirements

No prior qualifications are needed for learners to enrol in this course.

Career path

After completing this course, you can pursue the following career pathways:

  • Data Scientist - Average Salary: £40,000 - £60,000
  • Machine Learning Engineer - Average Salary: £50,000 - £70,000
  • Data Analyst - Average Salary: £30,000 - £45,000
  • Research Scientist - Average Salary: £45,000 - £65,000
  • Algorithm Developer - Average Salary: £45,000 - £55,000

Questions and answers

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Legal information

This course is advertised on Reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.

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.
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