Do you want to know why data science has been labeled the sexiest profession of the 21st century? After taking this course, you will be able to answer this question, understand what data science is and what data scientists do, and learn about career paths in the field.
The art of uncovering insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and accurately predicted the Nile River's flooding every year. Since then, people have continued to use data to derive insights and predict outcomes. Recently, they have carved out a unique and distinct field for the work they do. This field is data science.
In today's world, we use Data Science to find patterns in data and make meaningful, data-driven conclusions and predictions.
This course is for everyone and teaches concepts like how data scientists use machine learning and deep learning and how companies apply data science in business.
You will meet several data scientists, who will share their insights and experiences in data science. By taking this introductory course, you will begin your journey into this thriving field.
Overview
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.
- Data Science Topics
- 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.
- Applications and Careers in 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.
- Data literacy for Data Science (Optional)
- 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.
Taught by
Alex Aklson
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Reviews
3.8 rating, based on 4 Class Central reviews
4.7 rating at Coursera based on 73430 ratings
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Very short introduction to data science. No tools and techniques so far, no statistical or programming background. Just the idea and roots of data science explained. The videos and some point of views are quite interesting, but I'd not call it precisely a course, because there are no knowledge or skills to be learned here.
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BonnyStarted this through Coursera and then realized I could take it for free (exact same class) through CognitiveClass.ai.
Basic information which required no studying, just watching videos and remembering what was presented.
I preferred the CognitiveClass.ai version as it came with an IBM badge and certification, plus I could read the transcripts quickly and move to the next section without having to watch the entire video.
Either way it was a simple course that I completed in maybe 90 minutes with a score of 100%. -
Aiena MehtaThis course gives a decent overview about data science.
I personally liked the personal stories of the professor at University of Toronto. -
Maria Clarissa FionalitaNice simple introductory course to Data Science. Helped me learn the basic jargons that every data science noob need to know.
