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Data Cleaning and Processing for Data Scientists

Saravanan Dhandapani

Data Scientists spend most of their time cleaning and processing their data before they can be leveraged for future predictions. This course will teach you the various data cleaning and processing techniques and how to leverage the cloud services and AI tools to accomplish them.

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Data Scientists spend most of their time cleaning and processing their data before they can be leveraged for future predictions. This course will teach you the various data cleaning and processing techniques and how to leverage the cloud services and AI tools to accomplish them.

Properly cleaning and processing the data is crucial to ensure that the subsequent data modeling produces accurate, meaningful, and reliable data.

In this course, Data Cleaning and Processing for Data Scientists, you’ll gain the ability to learn the various techniques to pre-process the data that can be used to generate accurate analysis, which will lead to effective decision-making.

First, you’ll explore the various data-cleaning techniques and address data with missing values, duplicate data, and outliers.

Next, you’ll discover some of the transformation techniques like min-max scaler, standard scaler, one-hot encoding, and dimensionality reduction.

Finally, you’ll learn how to leverage the cloud services and AI tools and automate these tasks to achieve results quickly.

When you’re finished with this course, you’ll have the skills and knowledge of cleaning and processing the data needed to generate high-quality data for enhanced decision-making.

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What's inside

Syllabus

Course Overview
Data Cleaning Techniques and Strategies
Data Transformation Techniques and Strategies

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops data cleaning techniques used in industry, which are foundational for real-world application
Leverages cloud services and AI tools, which are in high demand for skilled data scientists
Teaches data transformation techniques used in the industry, which augments the cleaning techniques to make the data ready for analysis
Taught by instructors with a strong reputation, which adds credibility to the material
Focuses heavily on cleaning and processing tasks for data scientists, which aligns with the target audience

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Career center

Learners who complete Data Cleaning and Processing for Data Scientists will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists are in high demand as businesses increasingly rely on data to make decisions. This course will teach you the skills you need to clean and process data, which is a critical part of the data science process. By taking this course, you'll be well-positioned for a successful career as a Data Scientist.
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make better decisions. This course will teach you the skills you need to clean and process data, which is a critical part of the data analysis process. By taking this course, you'll be well-positioned for a successful career as a Data Analyst.
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. This course will teach you the skills you need to clean and process data, which is a critical part of the machine learning process. By taking this course, you'll be well-positioned for a successful career as a Machine Learning Engineer.
Business Analyst
Business Analysts use data to help businesses make better decisions. This course will teach you the skills you need to clean and process data, which is a critical part of the business analysis process. By taking this course, you'll be well-positioned for a successful career as a Business Analyst.
Data Engineer
Data Engineers build and maintain data pipelines. This course will teach you the skills you need to clean and process data, which is a critical part of the data engineering process. By taking this course, you'll be well-positioned for a successful career as a Data Engineer.
Statistician
Statisticians collect, analyze, and interpret data. This course will teach you the skills you need to clean and process data, which is a critical part of the statistical process. By taking this course, you'll be well-positioned for a successful career as a Statistician.
Data Architect
Data Architects design and build data systems. This course will teach you the skills you need to clean and process data, which is a critical part of the data architecture process. By taking this course, you'll be well-positioned for a successful career as a Data Architect.
Database Administrator
Database Administrators manage and maintain databases. This course will teach you the skills you need to clean and process data, which is a critical part of the database administration process. By taking this course, you'll be well-positioned for a successful career as a Database Administrator.
Software Engineer
Software Engineers design, develop, and maintain software applications. This course will teach you the skills you need to clean and process data, which is a common task for Software Engineers. By taking this course, you'll be well-positioned for a successful career as a Software Engineer.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve business problems. This course will teach you the skills you need to clean and process data, which is a critical part of the operations research process. By taking this course, you'll be well-positioned for a successful career as an Operations Research Analyst.
Financial Analyst
Financial Analysts use data to make investment decisions. This course will teach you the skills you need to clean and process data, which is a critical part of the financial analysis process. By taking this course, you'll be well-positioned for a successful career as a Financial Analyst.
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior. This course will teach you the skills you need to clean and process data, which is a critical part of the market research process. By taking this course, you'll be well-positioned for a successful career as a Market Researcher.
Product Manager
Product Managers develop and manage products. This course will teach you the skills you need to clean and process data, which is a common task for Product Managers. By taking this course, you'll be well-positioned for a successful career as a Product Manager.
Project Manager
Project Managers plan and execute projects. This course will teach you the skills you need to clean and process data, which is a common task for Project Managers. By taking this course, you'll be well-positioned for a successful career as a Project Manager.
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. This course will teach you the skills you need to clean and process data, which is a critical part of the business intelligence process. By taking this course, you'll be well-positioned for a successful career as a Business Intelligence Analyst.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Cleaning and Processing for Data Scientists.
Offers a practical approach to data cleaning and transformation, focusing on real-world examples and case studies.
Explores advanced data cleaning techniques using machine learning algorithms, providing insights into automated data cleaning approaches.
Focuses on data cleaning in the R programming language, offering a practical guide to data manipulation and transformation.
Provides a comprehensive overview of data cleaning and transformation using the Pandas library in Python.
Delves into advanced data cleaning techniques, including outlier detection, feature engineering, and data integration.
Emphasizes the importance of data quality in data science and provides guidance on data cleaning and validation.
Combines theoretical concepts with practical examples to demonstrate data cleaning techniques for machine learning applications.
Presents a step-by-step guide to data cleaning and transformation using Python, including code snippets and examples.

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