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Cheng-Han Lee and Miriam Swords Kalk

We built this program with expert analysts and scientists at leading technology companies to ensure you master the exact skills necessary to build a career in data science.

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We built this program with expert analysts and scientists at leading technology companies to ensure you master the exact skills necessary to build a career in data science.

Learn to organize data, uncover patterns and insights, make predictions using machine learning, and clearly communicate critical findings.

Download the Program Syllabus to learn more!

  • Programming experience (preferably in Python)
  • An understanding of programming concepts such as variables, functions, loops, and basic data structures like lists and dictionaries
  • Note: There is an optional Python Programming course in the program for those without Python programming experience.
  • Programming experience (preferably in Python)
  • An understanding of programming concepts such as variables, functions, loops, and basic data structures like lists and dictionaries
  • Note: There is an optional Python Programming course in the program for those without Python programming experience.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides a curriculum developed with industry partners to ensure students master cutting-edge skills
Prepares learners for a career in the in-demand field of Data Science
Taught by industry experts and scientists
Designed for learners with programming experience, preferably in Python
Includes an optional Python Programming course for those without prior experience
Content aligns with the skills and knowledge required for a successful career in Data Science

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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 Data Analyst Nanodegree with these activities:
Brush up on python programming
Refresh your understanding of basic programming concepts like variables, functions, and data structures to enhance your grasp of the upcoming topics.
Browse courses on Python
Show steps
  • Review online tutorials or documentation on Python syntax and data types.
  • Complete practice problems or coding challenges to reinforce your understanding.
  • Create a small Python program to demonstrate your proficiency.
Read 'Data Science for Business'
Gain a comprehensive understanding of data science concepts and applications in a business context.
Show steps
  • Read the book thoroughly, taking notes and highlighting key concepts.
  • Complete the exercises and case studies provided in the book.
  • Summarize the main takeaways and how they relate to the course material.
Attend data science meetups and conferences
Connect with professionals in the field, learn about industry trends, and expand your network.
Show steps
  • Identify relevant meetups or conferences in your area.
  • Attend events and actively participate in discussions.
  • Follow up with individuals you meet and explore potential collaborations.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a study group
Connect with peers to discuss course concepts, share insights, and support each other's learning journey.
Show steps
  • Reach out to classmates and form a study group.
  • Establish a regular meeting schedule and agenda.
  • Collaborate on assignments, review materials, and prepare for assessments.
Explore data visualization techniques
Enhance your understanding of data visualization principles and tools to effectively communicate insights from your data analysis.
Browse courses on Data Visualization
Show steps
  • Follow online tutorials on data visualization best practices.
  • Experiment with different data visualization tools and libraries.
  • Create interactive visualizations to showcase your skills.
Contribute to an open-source data science project
Expand your knowledge and gain practical experience by contributing to real-world data science projects.
Show steps
  • Identify an open-source data science project that aligns with your interests.
  • Review the project documentation and contribute code, documentation, or bug fixes.
  • Collaborate with project maintainers and the community.
Build a data analysis portfolio
Showcase your data analysis skills by creating a portfolio of projects that demonstrate your proficiency in data cleaning, analysis, and visualization.
Show steps
  • Identify real-world datasets relevant to your interests or career goals.
  • Perform data cleaning and analysis using appropriate techniques and tools.
  • Develop data visualizations to present your findings in a clear and engaging manner.
  • Write a brief report summarizing your project, including your methods and results.
Participate in a data science hackathon
Put your skills to the test and collaborate with others to solve real-world data challenges.
Show steps
  • Identify a relevant hackathon and form a team.
  • Gather and analyze data to develop a solution.
  • Build and present your prototype to a panel of judges.

Career center

Learners who complete Data Analyst Nanodegree will develop knowledge and skills that may be useful to these careers:
Data Analyst
The Data Analyst Nanodegree program is designed to equip you with the skills and knowledge necessary to succeed in the field of data analysis. The program covers a wide range of topics, including data organization, data analysis, machine learning, and data visualization. This course will help you build a strong foundation in the fundamentals of data analysis and prepare you for a successful career in this field.
Data Scientist
The Data Analyst Nanodegree program provides a solid foundation for those looking to pursue a career in data science. The program covers many of the core concepts and skills required for success in this field, including data analysis, machine learning, and data visualization. This course will help you build a strong foundation in the fundamentals of data science and prepare you for a successful career in this field.
Operations Research Analyst
The Data Analyst Nanodegree program may be useful for those looking to pursue a career in operations research. The program covers a range of topics that are relevant to this field, including data analysis, optimization, and modeling. This course can help you build a foundation in the skills and knowledge necessary for success in operations research.
Statistician
The Data Analyst Nanodegree program may be useful for those looking to pursue a career as a statistician. The program covers a range of topics that are relevant to this field, including data analysis, statistical modeling, and probability theory. This course can help you build a foundation in the skills and knowledge necessary for success as a statistician.
Software Engineer
The Data Analyst Nanodegree program may be useful for those looking to pursue a career in software engineering. The program covers a range of topics that are relevant to this field, including programming, data structures, and algorithms. This course can help you build a foundation in the skills and knowledge necessary for success in software engineering.
Financial Analyst
The Data Analyst Nanodegree program may be useful for those looking to pursue a career in financial analysis. The program covers a range of topics that are relevant to this field, including data analysis, data visualization, and communication. This course can help you build a foundation in the skills and knowledge necessary for success in financial analysis.
Product Manager
The Data Analyst Nanodegree program may be useful for those looking to pursue a career as a product manager. The program covers a range of topics that are relevant to this field, including data analysis, product development, and market research. This course can help you build a foundation in the skills and knowledge necessary for success as a product manager.
Consultant
The Data Analyst Nanodegree program may be useful for those looking to pursue a career as a consultant. The program covers a range of topics that are relevant to this field, including data analysis, problem solving, and communication. This course can help you build a foundation in the skills and knowledge necessary for success as a consultant.
Data Engineer
The Data Analyst Nanodegree program may be useful for those looking to pursue a career in data engineering. The program covers a range of topics that are relevant to this field, including data management, data warehousing, and data integration. This course can help you build a foundation in the skills and knowledge necessary for success in data engineering.
Quantitative Analyst
The Data Analyst Nanodegree program may be useful for those looking to pursue a career in quantitative analysis. The program covers a range of topics that are relevant to this field, including data analysis, statistical modeling, and financial modeling. This course can help you build a foundation in the skills and knowledge necessary for success in quantitative analysis.
Actuary
The Data Analyst Nanodegree program may be useful for those looking to pursue a career as an actuary. The program covers a range of topics that are relevant to this field, including data analysis, statistical modeling, and financial modeling. This course can help you build a foundation in the skills and knowledge necessary for success as an actuary.
Entrepreneur
The Data Analyst Nanodegree program may be useful for those looking to pursue a career as an entrepreneur. The program covers a range of topics that are relevant to this field, including data analysis, market research, and business planning. This course can help you build a foundation in the skills and knowledge necessary for success as an entrepreneur.
Market Researcher
The Data Analyst Nanodegree program may be useful for those looking to pursue a career in market research. The program covers a range of topics that are relevant to this field, including data analysis, data visualization, and communication. This course can help you build a foundation in the skills and knowledge necessary for success in market research.
Data Science Manager
The Data Analyst Nanodegree program may be useful for those looking to pursue a career as a data science manager. The program covers a range of topics that are relevant to this field, including data management, data analysis, and team leadership. This course can help you build a foundation in the skills and knowledge necessary for success as a data science manager.
Business Analyst
The Data Analyst Nanodegree program may be useful for those looking to pursue a career in business analysis. The program covers a range of topics that are relevant to this field, including data analysis, data visualization, and communication. This course can help you build a foundation in the skills and knowledge necessary for success in business analysis.

Reading list

We've selected 12 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 Analyst Nanodegree.
Provides a comprehensive introduction to statistical learning methods, making it a valuable resource for data analysts.
Provides a comprehensive guide to using R for data science, covering topics such as data manipulation, data visualization, and machine learning.
Provides a comprehensive guide to using Python for machine learning, covering topics such as data preparation, model selection, and evaluation.
Provides a comprehensive guide to using Python for machine learning, covering topics such as data preparation, model selection, and evaluation.
Provides a comprehensive guide to using Python for data analysis, covering topics such as data manipulation, data visualization, and machine learning.
Provides an accessible introduction to predictive analytics concepts and techniques, making it a valuable resource for data analysts.
Provides a gentle introduction to machine learning concepts and algorithms, making it accessible to beginners.
Provides an accessible introduction to data analytics concepts and techniques, covering topics such as data collection, data cleaning, data analysis, and data visualization.

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