What is Data Science?

Go to Course: https://www.coursera.org/learn/what-is-datascience

Introduction

# Course Review: What is Data Science? on Coursera In a world increasingly dominated by data, understanding the fundamentals of data science is vital for anyone looking to thrive in today's job market. Coursera’s course, **What is Data Science?**, offers a comprehensive introduction to this captivating field, regarded as the "sexiest profession of the 21st century." This course is not just for those wanting to become data scientists; it's also an essential primer for anyone looking to engage thoughtfully with data in their career. ## Course Overview This course seeks to answer critical questions: What exactly is data science? What roles do data scientists play, and what skills do they require? Additionally, it sheds light on the various career paths available in this burgeoning field. The course emphasizes both the historical context of data analysis—dating back to ancient civilizations—and contemporary practices, providing a thorough grounding in the subject matter. ## Module Breakdown ### Module 1: Defining Data Science and What Data Scientists Do This module sets the stage by discussing the diverse perspectives of industry professionals on what data science represents. Lesson 1 uncovers the variety of roles that data scientists undertake and highlights key processes they follow to interpret data meaningfully. By the end of this module, students will appreciate not only the definition of data science but also the skills and daily tasks of data scientists, from data analysis to algorithm application. ### Module 2: Data Science Topics In this module, students explore the impact of big data on business, society, and various sectors, including sports. The lessons cover the basics of big data, cloud computing, and the data mining process with practical examples. Furthermore, it gives an insightful look into machine learning and deep learning, illuminating how artificial intelligence has intertwined with data science. These lessons encourage students to think critically about the challenges and opportunities big data presents. ### Module 3: Applications and Careers in Data Science Here, the course shifts its focus to real-world applications of data science. The first lesson discusses how organizations harness data science to influence business strategies, enhance efficiency, and even save lives. The second lesson prepares students for the job market, detailing what employers seek in aspiring data scientists and helping learners strategize their career paths. This module culminates in a peer-reviewed final project that involves analyzing a job posting and applying learned concepts to identify requirements for data science roles. ### Optional Module: Data Literacy for Data Science For those seeking to solidify their data understanding, this optional module covers data literacy essentials. It discusses how data is generated, stored, and accessed while diving deeper into data repositories and the processes involved in handling large datasets. Although optional, it is highly recommended for those who wish to build a robust foundation in handling data. ## Course Recommendations ### Pros: 1. **Engaging Content**: The course provides a captivating narrative around data science, making it accessible for beginners and seasoned professionals alike. 2. **Diverse Learning Formats**: With various lessons involving video lectures, practical examples, and peer-reviewed projects, the course caters to different learning styles. 3. **Career-Oriented**: The focus on applications and career paths provides students with a pragmatic view of how to leverage data science in the workforce. 4. **Expert Insights**: Hearing from professionals in the field adds credibility and real-world relevance to the course materials. ### Cons: 1. **Introduction Level**: While it serves as an excellent primer, those with prior data science knowledge may find the course too basic. 2. **Time Commitment**: As with most online courses, students need to factor in time management as they navigate through the modules. ## Final Thoughts In conclusion, **What is Data Science?** on Coursera is a worthwhile investment for anyone looking to understand the essentials of this dynamic and impactful field. Whether you are considering a career shift to data science, enhancing your current skill set, or simply curious about data-driven decisions, this course provides the foundation and insights needed to navigate the world of data science confidently. With a thoughtful blend of theory and practical application, it equips learners to unlock a myriad of opportunities that data science presents. Highly recommended!

Syllabus

Defining Data Science and What Data Scientists Do

In Module 1, you delve into some fundamentals of Data Science. In lesson 1, you listen to how other professionals in the field define what data science is to them and the paths they took to consider data science as a career for themselves. You explore different roles data scientists fulfill, how data analysis is used in data science, and how data scientists follow certain processes to answer questions with that data. Moving on to Lesson 2, the focus shifts to the daily activities of data scientists. This encompasses learning about various real-world data science problems that professionals solve, the skills and qualities needed to be a successful data scientist, and opinions on how “big data” relates to those skills. You also learn a little about various data formats data scientists work with and algorithms used in the field to process data.

In the first lesson in this module, you gain insight into the impact of big data on various aspects of society, from business operations to sports, and develop an understanding of key attributes and challenges associated with big data. You will learn about the big data fundamentals, how data scientists use the cloud to handle big data, and the data mining process. Lesson two delves into machine learning and deep learning and the relationship of artificial intelligence to data science.

In the first lesson, you learn about the power of data science applications and how organizations leverage this power to drive business goals, improve efficiency, make predictions, and even save lives. You also reviewed the process you will follow as a data scientist to help your organization accomplish these ends. In the second lesson, you investigate what companies seek in a competent, experienced data scientist. You will learn how to position yourself to get hired as a data scientist. Amidst the diverse backgrounds from which data scientists emerge, you identify the qualities they share and skills that consistently set them apart from other data-related roles. You will complete a peer-reviewed final project by looking at a job posting for data scientist and identifying commonalities between the job and what you learned in this course. You will also walk through a case study, where you learn about Sarah and her data science journey.

This optional module focuses on understanding data and data literacy and is intended to supplement what you learned in the first three modules. As a data scientist, you will need to understand the ecosystem in which your data lives and how it gets manipulated to analyze it. This module introduces you to some of these fundamentals. In lesson one, you explore how data can be generated, stored, and accessed.  In lesson two, you take a deeper dive into data repositories and processes for handling massive data sets.