Booking options
£5
£5
On-Demand course
1 hour
All levels
Accredited by CPDQE
Learn how to clean, process, wrangle, and manipulate data
Know how to create a resume for a data science job
Get a grasp of NumPy by learning how to use it for numerical data
Uncover the secret of different Python libraries, such as Pandas, Matplotlib, SciPy and many more
Explore machine learning concepts and algorithms
Discover developing custom data solutions
You can create various applications for science, math, machine learning, and data science with Python. As a high-level, general-purpose programming language, Python is quite English-like and easy to learn. This Python for Data Science and Machine Learning course will show you how to use Python for machine learning and data science.
During the course, you will master every useful Python skill you need for data science and machine learning. If you find it challenging to write complex Python programs, we’ll show you how to do so with our step-by-step instructions based on actual work contexts. You’ll also learn how to run the regression, classification, and clustering and the specifics of supervised and unsupervised machine learning. Moreover, this course covers how statistics work for data science, hypothesis testing, and much more.
An expert instructor designed this “Python for Data Science and Machine Learning” course to provide you with the best learning experience possible. Our goal is for you to learn and apply the lessons from this course to improve your skills.
To become a master of Python, Enrol Now!
This course is CPDQE accredited, which serves as an impactful mechanism for skill enhancement.
Continuing Professional Development (CPD) stands as a crucial, widely acknowledged method that aids individuals, organisations, and entire industries in staying current with their skills and knowledge.
CPD not only facilitates the elevation of global standards and benchmarks, aligning with the growing forces of globalisation and consumer expectations but also transforms learning into a deliberate and proactive process. It motivates professionals to uphold a consistently high level of performance and demonstrates their unwavering commitment to a specific job role or profession.
Course Curriculum
Introduction to Python for Data Science & Machine Learning from A-Z
Data Science & Machine Learning Concepts
Python For Data Science
Statistics for Data Science
Probability and Hypothesis Testing
NumPy Data Analysis
Pandas Data Analysis
Python Data Visualization
Introduction to Machine Learning
Data Loading & Exploration
Data Cleaning
Feature Selecting and Engineering
Linear and Logistic Regression
K Nearest Neighbours
Decision Trees
Ensemble Learning and Random Forests
Support Vector Machines
K-Means
PCA
Data Science Career
Yes, we offer free PDF Certificate upon course completion. Here is an example certificate that you will get after completing your course.
Yes, this course is accredited by CPDQE.
Continuing Professional Development (CPD) is a practice embraced by countless individuals across diverse industries and professions. Typically, professional organisations and institutes mandate CPD requirements, often specifying a specific number of annual CPD training hours.
In recent decades, the dedication to CPD has transcended the confines of traditional sectors and UK-based institutions, gaining global recognition and acceptance.
Continuing Professional Development (CPD) stands as a crucial, widely acknowledged method that aids individuals, organisations, and entire industries in staying current with their skills and knowledge.
CPD not only facilitates the elevation of global standards and benchmarks, aligning with the growing forces of globalisation and consumer expectations but also transforms learning into a deliberate and proactive process. It motivates professionals to uphold a consistently high level of performance and demonstrates their unwavering commitment to a specific job role or profession.
The majority of institutions and professional organisations establish Continuing Professional Development (CPD) goals, typically on an annual basis. These objectives are determined by accumulating CPD activities, which include participating in training courses, eLearning programs, events, and other structured learning experiences.
Most professional bodies employ CPD hours as their primary metric, and when CPD points or credits are utilised, they are typically in a direct 1:1 correlation with CPD hours. In simpler terms, one CPD point equates to one CPD hour.