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 Data Preprocessing for Feature Engineering. Dive deep into key topics such as data cleaning, transformation, and feature selection to unleash the power of data in decision-making. Gain actionable insights to navigate the complexities of the digital landscape with confidence. Equip yourself with essential skills to preprocess data effectively and extract valuable features for machine learning models. Stay ahead in the ever-evolving field of data science and make a significant impact in your organization. Join us and elevate your expertise in data preprocessing for feature engineering today!
Unlock the power of data with our Certified Professional Course in Data Preprocessing for Feature Engineering. Dive deep into the world of data manipulation, cleaning, and transformation to extract valuable insights. Learn essential techniques to prepare data for machine learning models and enhance predictive accuracy. Our comprehensive program covers data normalization, missing value imputation, outlier detection, and more. Gain hands-on experience with industry-standard tools and real-world datasets. Elevate your data preprocessing skills and boost your career prospects in the rapidly growing field of data science. Enroll now to become a certified expert in data preprocessing for feature engineering.
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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• Data Transformation
• Missing Data Imputation
• Outlier Detection
• Feature Scaling
• Feature Selection
• Dimensionality Reduction
• Encoding Categorical Variables
• Handling Imbalanced Data
• Data Normalization
Key Facts about the Certified Professional Course in Data Preprocessing for Feature Engineering
Learning Outcomes:
- Gain a deep understanding of data preprocessing techniques essential for feature engineering in data science. - Learn how to clean, transform, and manipulate raw data to prepare it for analysis and modeling. - Acquire hands-on experience with popular tools and libraries used in data preprocessing, such as Pandas and NumPy. - Develop the skills to identify and handle missing data, outliers, and other data quality issues effectively. - Master the art of feature selection and extraction to improve model performance and interpretability.Industry Relevance:
- Data preprocessing is a critical step in the data science pipeline, making this course highly relevant for aspiring data scientists and analysts. - Companies across various industries rely on feature engineering to extract meaningful insights from their data and make informed business decisions. - Completing this course will enhance your employability and open up opportunities in fields such as finance, healthcare, marketing, and more. - Stay ahead of the competition by mastering the latest techniques and best practices in data preprocessing for feature engineering.Unique Features:
- Taught by industry experts with real-world experience in data science and feature engineering. - Practical assignments and projects that simulate real-world data preprocessing challenges. - Interactive online sessions that allow for collaboration with peers and personalized feedback from instructors. - Access to a dedicated online learning platform with resources, tutorials, and community forums for continuous support. - Upon completion, receive a prestigious certification that validates your expertise in data preprocessing for feature engineering.Data preprocessing is a crucial step in the data analysis process, as it involves cleaning, transforming, and organizing raw data into a format that is suitable for analysis. The Certified Professional Course in Data Preprocessing for Feature Engineering equips individuals with the necessary skills to handle real-world data and extract meaningful insights from it.
According to a recent survey by Glassdoor, the demand for professionals with expertise in data preprocessing and feature engineering has increased by 30% in the UK over the past year. Employers are seeking candidates who can effectively clean and prepare data for machine learning models, as this is essential for accurate predictions and decision-making.
| Industry | Projected Growth |
|---|---|
| Data Science | 45% |
| Machine Learning | 50% |
| Artificial Intelligence | 55% |
Career path
| Career Roles | Key Responsibilities |
|---|---|
| Data Analyst | Clean and preprocess data for analysis |
| Machine Learning Engineer | Prepare data for training machine learning models |
| Data Scientist | Feature engineering for predictive modeling |
| Business Intelligence Analyst | Transform raw data into actionable insights |
| Data Engineer | Design and implement data pipelines for preprocessing |