Welcome to Week 1 of the Data Scientist's Toolbox! This course is an introduction to the tools and ideas that you will see throughout the rest of the Data Science track.
We believe that the key word in Data Science is "science". Our course track is focused on providing you with three things: (1) an introduction to the key ideas behind working with data in a scientific way that will produce new and reproducible insight, (2) an introduction to the tools that will allow you to execute on a data analytic strategy, from raw data in a database to a completed report with interactive graphics, and (3) on giving you plenty of hands on practice so you can learn the techniques for yourself.
This course will focus primarily on getting you set up with the appropriate tools and accounts you will need for the rest of the track and on giving you a solid grounding in the key conceptual ideas. If you feel like the material is basic, that is ok, you will see much more in depth treatment of each topic in the subsequent course in the track.
We are excited about the opportunity to attempt to scale Data Science education. We intend for the courses to be self contained, fast paced, and interactive. We intend to run them frequently to give people with busy schedules the opportunity to work on material at their own pace.
Please see the course syllabus for information about the quizes, the project, due dates, and grading. Don't forget to say hi on the message boards. The community developed around these courses is one of the best places to learn and the best things about taking a MOOC!
Jeff Leek and the Data Science Track Team
Welcome to Week 2 of the Data Scientist's toolbox! This will be the most lecture-intensive week of the course. The primary goal is to get you set up with R, Rstudio, Github, and the other tools we will use throughout the course track.
Remember that the course project is open and ongoing. With the skills you learn this week you should be able to start on the basic steps in the course project.
Good luck and have a great week!
Jeff Leek and the Data Science Track Team
Welcome to Week 3 of Obtaining Data! This week we will start to reduce the number of lectures so you can spend more time focusing on your course project. The lectures you do have will focus on conceptual issues behind study design and turning data into knowledge.
If you have trouble or want to explore issues in more depth, please seek out answers on the message boards. They are a great resource! If you happen to be a superstar who already gets it, please take the time to help your classmates by answering their questions as well. This is one of the best ways to practice using and explaining your skills to others. These are two of the key characteristics of excellent data scientists.
Good luck and have a great week!
Jeff Leek and the Data Science Track Team
Welcome to Week 4 of Obtaining Data! In this final week we will focus on peer grading of assignments.
Participating in peer grading is an amazing learning opportunity. It gives you a chance to learn things from your fellow students, pick up tips for explaning key ideas, and helping others to learn as well. We have focused our effort on making the rubric as objective and straightforward to implement as possible. If you have any issues please report them in the forums as described in the syllabus.
Thanks again for all of your efforts in the course, we are in the last stretch. Good luck and have a great week!
Jeff Leek and the Data Science Track Team
Congratulations on finishing the Data Scientist's Toolbox!
We have set the grading and released the Statements of Accomplishment for the Course. It might take a few hours/days for the statements to be disbursed to accounts.
A couple of other notes:
- The course will begin again immediately starting in a couple of days. If you are still interested in keeping in touch with your fellow learners, please enroll in the new course and keep the conversation going. You may also be an invaluable resource for new course takers!
- Keep your eye on Hopkins offerings from Coursera. All announcements about future offerings will be posted at: https://twitter.com/jhubiostat and https://simplystatistics.org/, https://twitter.com/simplystats.
- If you liked this course, please consider taking some of the other course offerings through the Data Science Track. If you have completed all the course work in this track you now have the tools you will need to take on the challenges in the rest of our courses or in other Statistics, Data Science, or Machine Learning courses you may encounter.
Thanks again for all of your efforts during the course of the class and best of luck in your career!
Jeff Leek and the Data Science Track Team