Data Visualization with Python & R for Engineers from Coursera

What's inside

Syllabus

Introduction to Data - Part 1

In this module, we will delve into the fundamental aspects of data, exploring its definition, significance, and the transformative journey from raw information to actionable insights. Through a series of engaging videos, we will unravel the mysteries of structured and unstructured data, unveiling their unique characteristics and applications. As we progress, the module unfolds the intricate steps of the data workflow, guiding through the pivotal stages of framing objectives, preparing data, analysis, interpretation, and effective communication of findings. Additionally, our exploration extends to the vast landscape of Big Data, unraveling its complexities through the lens of the Five Vs: Volume, Velocity, Variety, Veracity, and Value. By the end of this module, We will not only have a comprehensive understanding of the foundational concepts of data but also possess the essential skills to navigate the data-driven landscapes of today's digital era. Get ready to unlock the power of data and discover its profound impact on our world!

Introduction to Data - Part 2

In this module, we will dive into the world of data analytics. We'll learn how to find the right data for data analysis, considering factors like relevance and timeliness. Then, we'll explore the crucial step of preprocessing, where we’ll learn to clean and organize raw data effectively. From handling missing values to spotting outliers, we'll pick up essential skills to ensure the analysis is accurate and reliable. By the end of this module, we'll be all set to confidently select, process, and analyze data like a pro. Let's get started!

Introduction to Visualization

In this module, we'll explore how data visualization turns complex data into engaging stories. Building on our understanding of data's significance, we'll discover how visualization simplifies information and connects with diverse audiences. We’ll delve into creating various visualizations, from statistical plots to geographical graphs. By grasping different statistical graphs and their applications, you'll enhance your skills in sharing meaningful insights. Get ready to unlock the potential of visualization and enhance your ability to tell compelling data stories. Let's dive into this visually enlightening journey!

Basics of Python

In this module, we'll delve into the fundamentals of Python coding. We'll explore key concepts such as variables, data types, and structures — crucial components in creating robust code. Throughout your Python learning journey, you'll acquire the skill of decision-making through if-else statements, navigate data using loops, and enhance your code with custom functions. Whether you're a coding novice or have some prior knowledge, this course ensures hands-on, practical experience. Let's explore, learn, and become experts in the key principles of Python programming. Get ready to bring your coding ideas to life!

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops data mining, visualization techniques, Python; applicable to engineering, healthcare, and manufacturing

Taught by Sivarit Sultornsanee, who has expertise in data analytics and visualization

Suitable for beginners with no prior knowledge in data visualization

Career center

Learners who complete Data Visualization with Python & R for Engineers will develop knowledge and skills that may be useful to these careers:

Data Visualization Specialist

Data Visualization Specialists translate raw data into visually appealing and informative charts, graphs, and dashboards. They use their expertise in design, data visualization, and storytelling to create data visualizations that are both beautiful and effective. This course provides a strong foundation in data visualization and Python, two essential skills for Data Visualization Specialists.

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Data Analyst

Data Analysts translate raw data into digestible, actionable insights. They use their expertise in statistical analysis, data visualization, and programming to create powerful dashboards and reports that help businesses make informed decisions. This course provides a solid foundation in these key skills, making it an excellent choice for aspiring Data Analysts.

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Data Scientist

Data Scientists use their knowledge of machine learning, statistics, and programming to build predictive models and solve complex problems. This course provides a strong foundation in data visualization and Python, two essential skills for Data Scientists. Additionally, the course's focus on data exploration and storytelling can help Data Scientists communicate their findings more effectively.

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Data Engineer

Data Engineers build and maintain the infrastructure that supports data-driven organizations. They use their expertise in database management, cloud computing, and programming to ensure that data is accessible, reliable, and secure. This course provides a solid foundation in data visualization and Python, two skills that are essential for Data Engineers.

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Business Analyst

Business Analysts use data to understand and improve business processes. They use their expertise in data analysis, data visualization, and business acumen to identify opportunities for growth and efficiency. This course provides a solid foundation in data visualization and Python, two skills that are essential for Business Analysts.

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Product Manager

Product Managers are responsible for the development and launch of new products. They use their expertise in market research, data analysis, and design to create products that meet the needs of customers. This course provides a solid foundation in data visualization and Python, two skills that are increasingly important for Product Managers.

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Marketing Analyst

Marketing Analysts use data to understand and improve marketing campaigns. They use their expertise in data analysis, data visualization, and marketing to create campaigns that are both effective and efficient. This course provides a solid foundation in data visualization and Python, two skills that are essential for Marketing Analysts.

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Healthcare Data Analyst

Healthcare Data Analysts use their expertise in data analysis, data visualization, and healthcare to improve patient care and outcomes. This course may be useful for aspiring Healthcare Data Analysts, as it provides a solid foundation in data visualization and Python, two skills that are essential for this role.

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Financial Analyst

Financial Analysts use data to understand and predict financial trends. They use their expertise in data analysis, data visualization, and finance to make investment recommendations and develop financial plans. This course may be useful for aspiring Financial Analysts, as it provides a solid foundation in data visualization and Python, two skills that are increasingly important for this role.

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Operations Research Analyst

Operations Research Analysts use data to improve the efficiency and effectiveness of organizations. They use their expertise in data analysis, data visualization, and operations research to develop solutions to complex problems. This course may be useful for aspiring Operations Research Analysts, as it provides a solid foundation in data visualization and Python, two skills that are essential for this role.

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Actuary

Actuaries use data to assess and manage risk. They use their expertise in data analysis, data visualization, and actuarial science to develop insurance plans and financial products. This course may be useful for aspiring Actuaries, as it provides a solid foundation in data visualization and Python, two skills that are increasingly important for this role.

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Statistician

Statisticians use data to understand and interpret the world around us. They use their expertise in data analysis, data visualization, and statistics to develop new knowledge and solve problems. This course may be useful for aspiring Statisticians, as it provides a solid foundation in data visualization and Python, two skills that are increasingly important for this role.

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Data Architect

Data Architects design and manage the data infrastructure that supports data-driven organizations. They use their expertise in database management, cloud computing, and data modeling to ensure that data is accessible, reliable, and secure. This course may be useful for aspiring Data Architects, as it provides a solid foundation in data visualization and Python, two skills that are increasingly important for this role.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They use their expertise in programming, data structures, and algorithms to create software that meets the needs of users. This course may be useful for aspiring Software Engineers, as it provides a solid foundation in Python, a popular programming language for data visualization.

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Computer Scientist

Computer Scientists use their expertise in computer science to solve problems and create new technologies. They use their knowledge of programming, data structures, and algorithms to develop software, hardware, and other computing systems. This course may be useful for aspiring Computer Scientists, as it provides a solid foundation in Python, a popular programming language for data visualization.

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