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Intro to Analytic Thinking, Data Science, and Data Mining

Welcome to Introduction to Analytic Thinking, Data Science, and Data Mining. In this course, we will begin with an exploration of the field and profession of data science with a focus on the skills and ethical considerations required when working with data. We will review the types of business problems data science can solve and discuss the application of the CRISP-DM process to data mining efforts. A brief overview of Descriptive, Predictive, and Prescriptive Analytics will be provided, and we will conclude the course with an exploratory activity to learn more about the tools and resources you might find in a data science toolkit.

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What's inside

Syllabus

Data Science: The Field and Profession

Welcome to Module 1, Data Science: The Field and Profession. In this module, we will review data science as a field and explore the concepts of small and big data. We will also survey the skills of successful data scientists and discuss the types of business problems data scientists might be asked to solve in the near future.

Data Science in Business

Welcome to Module 2, Data Science in Business. In this module, we will take a closer look at the applications of data science in a business environment and discuss ethical considerations to keep in mind when working with data.

Data Mining and an Overview of Data Analytics

Welcome to Module 3, Data Mining and an Overview of Data Analytics. In this module we will begin with an explanation of CRISP-DM, a cross-industry standard process for data mining. We will also provide an introduction to descriptive, predictive and prescriptive analytics.

Solving Problems with Data Science

Welcome to Module 4, Solving Problems with Data Science. In this last module of the course we will explore some real-world applications of data science solutions and take a closer look at the types of tools and programs you might expect to see in a data science toolkit.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

This course introduces fundamentals of data science and analytics

Explores various applications of data science in a business environment

Examines the CRISP-DM process for data mining and provides an overview of descriptive, predictive, and prescriptive analytics

Showcases real-world applications of data science solutions

Introduces learners to tools and resources commonly used in data science

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Reviews summary

Strong fundamentals of data science

Learners say this course provides a solid foundation in the fundamentals of data science. According to students, it covers a wide range of topics, including data mining, analytic thinking, and data science tools. The course is well-structured with engaging assignments and informative readings. However, some learners found the material to be a bit too basic and lacking in lectures.

Covers essential data science concepts.

"It gives me overview about data science and the future"

"I consider this course a must for one's journey into Data Science."

"an amazing course"

Some quiz questions cover material not in readings.

"The knowledge asked in the first quiz, hasn't been mentioned before in the reading."

"The quiz for the 1st and 2nd module had a few questions that need information that wasn't included in the previews readings."

Primarily readings with few lectures.

"There were readings; no lectures."

"Too general introduction. too much reading but not enough lecture."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Intro to Analytic Thinking, Data Science, and Data Mining with these activities:

Python Refresher

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Brush up on your Python skills to prepare for this course's emphasis on data analysis and machine learning.

Browse courses on Python

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Review Python basics (data types, variables, control flow)
Practice writing simple Python scripts

Data Science for Business

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Gain a comprehensive understanding of data science applications in a business context.

View Data Science for Business: What You Need to... on Amazon

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Read the book's chapters on data science concepts and techniques
Reflect on how these concepts apply to real-world business scenarios

Introduction to Data Science with Python

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Supplement your understanding of data science concepts by following guided tutorials that provide hands-on experience.

Browse courses on Data Science

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Find a reputable tutorial series on data science with Python
Follow the tutorials step-by-step, completing all exercises and assignments
Seek clarification or assistance if needed

Five other activities

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Show all eight activities

Data Science Study Group

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Enhance your learning by collaborating with peers in a study group dedicated to data science.

Browse courses on Data Science

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Find or form a study group with fellow students
Schedule regular meetings to discuss course material, share insights, and work on projects together

Data Analysis Drills

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Reinforce your understanding of data analysis techniques by completing practice drills and exercises.

Browse courses on Data Analysis

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Identify datasets for analysis
Apply data analysis techniques (e.g., descriptive statistics, visualization)
Interpret and draw insights from the results

Data Science Resources Compilation

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Organize and expand your understanding of data science by compiling a collection of valuable resources.

Browse courses on Data Science

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Identify and gather relevant resources (e.g., books, articles, tutorials, datasets)
Organize the resources by topic or category
Annotate or summarize the resources for easy reference

Data Visualization Project

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Solidify your data visualization skills by creating a data visualization project that effectively communicates insights.

Browse courses on Data Visualization

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Gather and prepare data
Choose appropriate visualization techniques
Design and implement the visualization
Write a brief report interpreting the results

Data Science Hackathon

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Challenge yourself and test your data science skills by participating in a hackathon.

Browse courses on Data Science

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Find or register for a data science hackathon
Form a team or work individually
Develop and implement a data science solution within the specified time frame

Career center

Learners who complete Intro to Analytic Thinking, Data Science, and Data Mining will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist gathers and analyzes raw data to extract meaningful insights and trends. This course can help you build a foundation in the field of data science, providing you with an understanding of the skills and ethical considerations required for success. You will also gain insights into the types of business problems data scientists solve and learn about the CRISP-DM process used in data mining efforts.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst analyzes data to identify trends and patterns, providing valuable insights that can help businesses make better decisions. This course can help you develop the skills needed to succeed in this role, including data mining techniques, descriptive, predictive, and prescriptive analytics, and ethical considerations when working with data.

See salaries and explore the career path for Data Analyst

Business Analyst

A Business Analyst works with stakeholders to understand their business needs and identify opportunities for improvement. This course can help you develop the skills needed to communicate effectively with stakeholders and translate business goals into actionable data-driven insights.

See salaries and explore the career path for Business Analyst

Data Engineer

A Data Engineer designs, builds, and maintains the infrastructure needed to store and process data. This course can provide you with a foundational understanding of data science concepts and techniques, helping you design and implement efficient data pipelines.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

A Machine Learning Engineer develops and maintains machine learning models to solve complex business problems. This course can help you build a foundation in data science and machine learning, providing you with an understanding of the skills and ethical considerations required for success.

See salaries and explore the career path for Machine Learning Engineer

Data Architect

A Data Architect designs and implements data management solutions to ensure data quality and accessibility. This course can provide you with a comprehensive overview of data science concepts and techniques, helping you understand the principles of data architecture and how to design scalable and secure data solutions.

See salaries and explore the career path for Data Architect

Data Science Manager

A Data Science Manager leads and manages data science teams, overseeing the development and implementation of data science solutions. This course can help you understand the challenges and responsibilities of managing a data science team, providing you with insights into project management, leadership, and ethical decision-making.

See salaries and explore the career path for Data Science Manager

Data Visualization Engineer

A Data Visualization Engineer designs and creates data visualizations to communicate insights and trends in a visually appealing and easy-to-understand way. This course can help you develop the skills needed to succeed in this role, including data visualization techniques, storytelling with data, and ethical considerations when working with data.

See salaries and explore the career path for Data Visualization Engineer

Operations Research Analyst

An Operations Research Analyst uses mathematical and analytical techniques to solve complex business problems and improve efficiency. This course can provide you with a foundation in data science concepts and techniques, helping you understand how to apply data science to operations research problems.

See salaries and explore the career path for Operations Research Analyst

Financial Analyst

A Financial Analyst analyzes financial data to make investment recommendations and provide insights into financial trends. This course can provide you with a foundational understanding of data science concepts and techniques, helping you understand how to apply data science to financial analysis and modeling.

See salaries and explore the career path for Financial Analyst

Risk Analyst

A Risk Analyst identifies and assesses risks to businesses and develops strategies to mitigate those risks. This course can provide you with a foundation in data science concepts and techniques, helping you understand how to apply data science to risk management and modeling.

See salaries and explore the career path for Risk Analyst

Healthcare Data Analyst

A Healthcare Data Analyst analyzes healthcare data to identify trends and patterns, providing valuable insights that can help improve patient care and reduce costs. This course can provide you with a foundational understanding of data science concepts and techniques, helping you understand how to apply data science to healthcare data analysis.

See salaries and explore the career path for Healthcare Data Analyst

Market Research Analyst

A Market Research Analyst collects and analyzes data about markets and customers to provide insights that help businesses make better decisions. This course can provide you with a foundation in data science concepts and techniques, helping you understand how to apply data science to market research and analysis.

See salaries and explore the career path for Market Research Analyst

UX Researcher

A UX Researcher studies how users interact with products and services, providing insights that help improve the user experience. This course can provide you with a foundation in data science concepts and techniques, helping you understand how to apply data science to UX research and analysis.

See salaries and explore the career path for UX Researcher

Social Media Analyst

A Social Media Analyst analyzes data from social media platforms to understand customer behavior and trends. This course can provide you with a foundational understanding of data science concepts and techniques, helping you understand how to apply data science to social media analysis and marketing.

See salaries and explore the career path for Social Media Analyst

Reading list

We've selected 13 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 Intro to Analytic Thinking, Data Science, and Data Mining.

Data Mining

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Classic textbook on data mining. It covers all the major concepts and techniques in data mining, and it provides a wealth of examples and exercises.

Data Mining: Concepts and Techniques (The Morgan...

Kindle Edition

$$$

Data Mining: Concepts and Techniques (The Morgan...

Hardcover

$$$

Data Mining: Concepts and Techniques, Second...

Hardcover

Data Mining: Know It All

Hardcover

$$$

Build a Large Language Model (From Scratch)

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Provides a practical guide to machine learning for data scientists. It covers the basics of machine learning, and it provides a variety of case studies and examples.

Intro to Analytic Thinking, Data Science, and Data Mining

Three deals to help you save

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Strong fundamentals of data science

Activities

Career center

Reading list

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