Overview
This course is an excellent learning opportunity for those who are passionate about the topic and who are interested in a successful career within the relevant industry. Professionals currently working in this field who wish to brush up on their knowledge and advance their careers may also enrol in this program.
In the [su_post post_type="course"] Course, you will find a number of engaging, in-depth modules that will provide you with comprehensive theoretical knowledge that will enable you to succeed in your career. As proof of your completion, you will receive a free e-certificate from Learndrive.
Using computers, tablets, smartphones, and other internet-enabled devices, you can access the course modules at your own pace. Invest in your professional development today and learn skills that will lead to your dream job. Become a career leader by taking this course online.
- Premium Video Materials in bite-sized format for the most accessible learning experience
- Free e-certificate after completing the course
- Flexible study time and pace
- Instructor-led Course
Students can access the course using any internet-connected device through our online learning platform. You may study at your own pace since there are no formal deadlines or teaching schedules.
The learners who pass the course will receive a Learndrive Certificate as a badge of accomplishment. The e-certificate is free of charge. There is a small fee, however, if you want a hard copy of your certificate.
The course is right for you if you already work in this industry or want to make the transition. This [su_post post_type="course"] Course is designed to enhance your expertise and improve your CV.
Students from all backgrounds are welcome to participate in the online training. There are no requirements for participation. The only prerequisite for studying this [su_post post_type="course"] Course is an interest in learning and a good grasp of English, mathematics, and computer skills.
Suitable for
You will need
- A device with an internet connection
Course content
Introduction to Python for Data Science & Machine Learning from A-Z
- Who is this Course for – Learn Python
- DS + ML Marketplace
- Data Science Job Opportunities
- Data Science Job Roles
- What is a Data Scientist
- How To Get a Data Science Job
- Data Science Projects Overview
Data Science & Machine Learning Concepts
- Why We Use Python
- What is Data Science
- What is Machine Learning
- ML Concepts _ Algorithms
- What is Deep Learning
- Machine Learning vs Deep Learning
Python For Data Science
- What is Python Programming – Python for Data Science and Machine Learning
- Why Python for Data Science
- What is Jupyter
- What is Colab
- Jupyter Notebook
- Getting Started with Colab
- Python Variables, Booleans and None
- Python Operators
- Python Numbers and Booleans
- Python Strings
- Python Conditional Statements
- Python For Loops and While Loops
- Python Lists
- More About Python Lists
- Python Tuples
- Python Dictionaries
- Python Sets
- Compound Data Types and When to use each Data Type
- Functions – Learn Python
- Python Object Oriented Programming
- Care for a Feedback
Statistics for Data Science
- Intro to Statistics
- Descriptive Statistics
- Measure of Variability
- Measure of Variability Continued
- Measures of Variable Relationship
- Inferential Statistics
- Measures of Asymmetry
- Sampling Distribution
Probability and Hypothesis Testing
- What Exactly Probability
- Expected Values
- Relative Frequency
- Hypothesis Testing Overview
NumPy Data Analysis
- NumPy Array Data Types
- NumPy Arrays – Learn Python
- NumPy Array Basics
- NumPy Array Indexing
- NumPy Array Computations
- Broadcasting – Learn Python
Pandas Data Analysis
- Intro to Pandas
- Intro to Panda Continued
Python Data Visualization
- Data Visualization Overview
- Different Data Visualization Libraries in Python
- Python Data Visualization Implementation
Introduction to Machine Learning
- Intro to ML
Data Loading & Exploration
- Exploratory Data Analysis
Data Cleaning
- Feature Scaling
- Data Cleaning
Feature Selecting and Engineering
- Feature Engineering
Linear and Logistic Regression
- Linear Regression Intro
- Gradient Descent
- Linear Regression + Correlation Methods
- Linear Regression Implementation
- Logistic Regression
K Nearest Neighbours
- KNN Overview
- Parametic vs Non-Parametic Models
- EDA on Iris Dataset
- KNN – Intuition
- Implement the KNN algorithm from scratch
- Compare the Result with Sk learn Library
- KNN Hyperparameter tuning using the cross-validation
- The decision boundary visualization
- KNN – Manhattan vs Euclidean Distance
- KNN Scaling in KNN
- Curse of dimensionality
- KNN use cases
- KNN pros and cons
Decision Trees
- Decision Trees Section Overview
- EDA on Adult Dataset – Learn Python
- What is Entropy and Information Gain
- The Decision Tree ID3 algorithm from scratch Part 1
- The Decision Tree ID3 algorithm from scratch Part 2
- The Decision Tree ID3 algorithm from scratch Part 3
- ID3 – Putting Everything Together
- Evaluating our ID3 implementation
- Compare with Sk learn implementation – Learn Python
- Visualizing the Tree
- Plot the features importance
- Decision Trees Hyper-parameters
- Pruning
- [Optional] Gain Ration
- Decision Trees Pros and Cons
- [Project] Predict whether income exceeds $50Kyr – Overview
Ensemble Learning and Random Forests
- Ensemble Learning Section Overview
- What is Ensemble Learning
- What is Bootstrap Sampling
- What is Bagging
- Out-of-Bag Error
- Implementing Random Forests from scratch Part 1
- Implementing Random Forests from scratch Part 2
- Compare with sk learn implementation 2 – Learn Python
- Random Forests Hyper-Parameters
- Random Forests Pros and Cons
- What is Boosting
- AdaBoost Part 1
- AdaBoost Part 2
Support Vector Machines
- SVM – Outline
- SVM – SVM intuition
- SVM – Hard vs Soft Margin
- SVM – C HP
- SVM – Kernel Trick
- SVM – Kernel Types
- SVM – Linear Dataset
- SVM – Non-Linear Dataset
- SVM with Regression
- SVM – Project Overview
K-Means
- Unsupervised Machine Learning Intro
- Representation of Clusters
- Data Standardization
PCA
- PCA – Section Overview
- What is PCA
- PCA – Drawbacks
- PCA – Algorithm Steps
- PCA – Cov vs SVD
- PCA – Main Applications
- PCA – Image Compression Scratch
- PCA – Data Pre processing Scratch
- PCA – BiPlot
- PCA – Feature Scaling and Screeplot
- PCA – Supervised vs unsupervised
- PCA – Visualization
Data Science Career
- Creating a Data Science Resume
- Data Science Cover Letter
- How To Contact Recruiters
- Getting Started with Freelancing – Learn Python
- Top Freelance Websites – Learn Python
- Personal Branding – Learn Python
- Networking Do_s and Don_ts – Learn Python
- Importance of a Website – Learn Python
Final Quiz: Python for Data Science and Machine Learning
- Final Quiz: Python for Data Science and Machine Learning
Order Your Transcript
- Order Your Transcript
Assessment Test
- Python for Data Science and Machine Learning Assessment Test
How the course works
-
Get access
After payment, the course appears in your LearnDrive dashboard.
-
Learn at your pace
Work through 144 short video lessons in one sitting or several.
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Complete the assessment
Attend the assessment and secure 70% to pass the assessment test.
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Get your documents
Download the PDF document(s) included in your package.
Certificate and accreditation
What you receive
A digital Certificate of Completion (PDF) for this CPDQE-accredited course.
What the accreditation means
CPDQE accredits this course for continuing professional development (CPD). CPD accreditation is not a regulated qualification and does not by itself confirm job competence.
Checking a certificate
Anyone can check a certificate code on the LearnDrive certificate verification page.
What each package includes
| Document | Package 1 · £20.00 | Package 2 · £29.00 |
|---|---|---|
| Course access | Lifetime access | Lifetime access |
| Certificate of Completion (PDF) | Included | Included |
| Transcript (PDF) | Not included | Included |
| Enrolment Letter (PDF) | Not included | Included |
Course provider
LearnDrive Courses
LearnDrive is a UK-based online learning provider run by Edtech Learning Ltd. Courses are built by an in-house instructional design team using short video and audio modules.
About LearnDriveReviews
Reviews for this course
Reviews appear here when learners who completed this course leave one.
Frequently asked questions
When can I start after paying?
Straight away. Access is given as soon as your payment is processed, and the course appears in your dashboard.
How long can I access the course?
For life. Once you have enrolled, the course stays in your dashboard and you can come back to it whenever you like.
Do I need any prior knowledge?
No. The course starts from the basics, so you can begin without any previous experience of the topic.
Is there an assessment, and can I retake it?
Yes. There is a short assessment at the end and you need 70% to pass. If you do not pass first time, you can retake it.
Which documents does each package include?
It depends on the package you choose. The "What each package includes" table on this page shows exactly which PDF documents come with each one.
Are there extra costs for printed documents or delivery?
Your package includes digital PDF documents. If you would like printed copies, contact us and we will tell you the options and any costs.
What is the refund policy?
You can request a refund within 14 days of purchase. We follow a no-questions-asked refund policy.
How do I use a voucher?
Go to the voucher redemption page, enter your details and paste your voucher code (do not type it manually), then click Send. Your login details arrive by email and the course will be waiting in your dashboard.
How do I get help?
Our support team is happy to help. Get in touch through the contact page or call +44 7897 721446.
