Duration
The programme is available in two duration modes:
Fast track - 1 month
Standard mode - 2 months
Course fee
The fee for the programme is as follows:
Fast track - 1 month: £140
Standard mode - 2 months: £90
Assessment mode
Assignments or Quiz
Tutor support available
International Students can apply
Students from over 90 countries
Flexible study
Study anytime, from anywhere
Overview
Professional Certificate in Feature Engineering and Data Analysis
This comprehensive program is designed for aspiring data professionals looking to master feature engineering and data analysis techniques. Gain in-depth knowledge in data preprocessing, feature selection, and statistical analysis to enhance predictive modeling and decision-making. Ideal for data scientists, machine learning engineers, and business analysts seeking to advance their skills in data manipulation. Unlock new career opportunities in the data-driven world with this Professional Certificate.
Start your learning journey today!
Data Science Training: Dive into the world of feature engineering and data analysis skills with our Professional Certificate program. Learn to extract valuable insights from data through hands-on projects and real-world examples. Gain practical skills in manipulating data, creating new features, and preparing datasets for analysis. This machine learning training course offers self-paced learning, allowing you to study at your own convenience. Stay ahead in the competitive field of data science by mastering the art of feature engineering and data analysis. Enroll now to take your career to the next level!Get free information
Course structure
• Introduction to Feature Engineering • Data Preprocessing Techniques • Exploratory Data Analysis • Feature Selection Methods • Feature Transformation Techniques • Handling Missing Data • Outlier Detection and Treatment • Feature Scaling and Normalization • Dimensionality Reduction TechniquesMaster the art of Feature Engineering and Data Analysis with our Professional Certificate program. This intensive course is designed to equip you with the essential skills needed to excel in the field of data science and analytics. By the end of the program, you will be able to manipulate data effectively, extract valuable insights, and create predictive models using advanced techniques.
The duration of the Professional Certificate in Feature Engineering and Data Analysis is 10 weeks, with a self-paced learning format that allows you to study at your own convenience. Whether you are a beginner or an experienced professional looking to upskill, this program is suitable for anyone interested in advancing their career in data analysis.
Our curriculum is carefully crafted to be aligned with current industry trends and best practices. You will learn how to work with real-world data sets, apply feature engineering principles, and conduct in-depth data analysis using popular tools and technologies. This program will not only enhance your technical skills but also make you stand out in today's competitive job market.
| Year | Number of Data Breaches |
|---|---|
| 2018 | 198 |
| 2019 | 262 |
| 2020 | 366 |
The Professional Certificate in Feature Engineering and Data Analysis is crucial in today's market, especially in the UK where data breaches have been on the rise. According to the statistics provided, the number of data breaches in the UK has increased from 198 in 2018 to 366 in 2020. This highlights the pressing need for professionals with expertise in data analysis and feature engineering to prevent and mitigate such incidents.
By obtaining this certificate, individuals can enhance their skills in data analysis, allowing them to identify patterns, trends, and anomalies in datasets effectively. This knowledge is invaluable for organisations looking to strengthen their cybersecurity measures and protect sensitive information from cyber threats.
With the demand for professionals with data analysis and feature engineering skills on the rise, this certificate can significantly boost employability and career advancement opportunities in the data-driven market.