Python for Data Science and Machine Learning

Description

This course at a glance

• 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!

Accredited by

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