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
Embark on a transformative journey with our Certified Professional Course in Python for Feature Engineering. Dive deep into key topics such as data preprocessing, feature selection, and extraction techniques. Gain actionable insights to enhance your data analysis skills and stay ahead in the dynamic digital landscape. Learn how to leverage Python libraries for efficient feature engineering and unlock the full potential of your data. Empower yourself with practical knowledge and hands-on experience to drive impactful decision-making. Elevate your career prospects and become a sought-after data professional with our comprehensive course. Enroll now and take the first step towards mastering feature engineering in Python.
Unlock the power of Python for Feature Engineering with our Certified Professional Course. Dive deep into the world of data manipulation, extraction, and transformation to enhance your data analysis skills. Learn how to extract valuable insights from raw data using Python's advanced features and libraries. Our comprehensive program covers everything from data preprocessing to feature selection, ensuring you have the expertise to excel in the field. Join us and become a certified Python expert in Feature Engineering, ready to tackle real-world data challenges with confidence. Take the next step in your career and enroll today!
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Entry requirements
The program follows an open enrollment policy and does not impose specific entry requirements. All individuals with a genuine interest in the subject matter are encouraged to participate.Course structure
• Data Cleaning• Feature Selection
• Feature Scaling
• Handling Missing Values
• Encoding Categorical Variables
• Feature Extraction
• Dimensionality Reduction
• Handling Outliers
• Normalization
• Binning
The Certified Professional Course in Python for Feature Engineering is a comprehensive program designed to equip individuals with the necessary skills and knowledge to excel in the field of feature engineering using Python.
Upon completion of this course, participants will gain a deep understanding of feature engineering techniques, including data preprocessing, feature selection, and feature extraction. They will also learn how to apply these techniques to real-world datasets, enabling them to enhance the performance of machine learning models.
This course is highly relevant to industries such as data science, machine learning, and artificial intelligence, where feature engineering plays a crucial role in the success of predictive modeling projects. Professionals who are looking to advance their careers in these fields will greatly benefit from the practical skills and insights gained from this course.
One of the unique features of this course is its hands-on approach, which allows participants to apply their learning in a practical setting. Through a series of interactive exercises and projects, students will have the opportunity to work with real datasets and gain valuable experience in feature engineering.
Overall, the Certified Professional Course in Python for Feature Engineering is a must-have for individuals who are looking to enhance their expertise in feature engineering and stay ahead in the rapidly evolving field of data science. With its industry-relevant curriculum and practical focus, this course is sure to provide participants with the skills and confidence needed to succeed in their careers.
Upon completion of this course, participants will gain a deep understanding of feature engineering techniques, including data preprocessing, feature selection, and feature extraction. They will also learn how to apply these techniques to real-world datasets, enabling them to enhance the performance of machine learning models.
This course is highly relevant to industries such as data science, machine learning, and artificial intelligence, where feature engineering plays a crucial role in the success of predictive modeling projects. Professionals who are looking to advance their careers in these fields will greatly benefit from the practical skills and insights gained from this course.
One of the unique features of this course is its hands-on approach, which allows participants to apply their learning in a practical setting. Through a series of interactive exercises and projects, students will have the opportunity to work with real datasets and gain valuable experience in feature engineering.
Overall, the Certified Professional Course in Python for Feature Engineering is a must-have for individuals who are looking to enhance their expertise in feature engineering and stay ahead in the rapidly evolving field of data science. With its industry-relevant curriculum and practical focus, this course is sure to provide participants with the skills and confidence needed to succeed in their careers.
Why Certified Professional Course in Python for Feature Engineering is Required?
Feature engineering is a crucial aspect of data science and machine learning, where Python is widely used for its versatility and efficiency. A certified professional course in Python for feature engineering is essential to equip individuals with the necessary skills to manipulate and extract meaningful features from data, leading to better model performance and insights.
Industry Demand for Certified Professionals in Python for Feature Engineering
| Statistic | Demand |
|---|---|
| According to Tech Nation | The demand for data professionals in the UK has increased by 231% over the past 5 years. |
| According to Glassdoor | The average salary for a data engineer in the UK is £55,000 per annum. |
Career path
| Career Roles | Key Responsibilities |
|---|---|
| Python Data Engineer | Developing data pipelines and ETL processes using Python for feature engineering. |
| Machine Learning Engineer | Building and optimizing machine learning models by creating relevant features. |
| Data Scientist | Utilizing Python for feature extraction, transformation, and selection in data analysis. |
| AI Research Scientist | Conducting research and experiments to improve feature engineering techniques in AI. |
| Big Data Analyst | Processing and analyzing large datasets using Python for feature engineering purposes. |