The second capstone session of the Johns Hopkins Data Science Specialization concluded recently. This time, we had 1,040 learners sign up to participate in the session, which again featured a project developed in collaboration with the amazingly innovative folks at SwiftKey.
We’ve identified the learners listed below as the top performers in this capstone session. This is an incredibly talented group of people who have worked very hard throughout the entire nine-course specialization. Please take some time to read their stories and look at their work.
Ben Apple is a Data Scientist and Enterprise Architect with the Department of Defense. Mr. Apple holds a MS in Information Assurance and is a PhD candidate in Information Sciences.
As a self trained data scientist I was looking for a program that would formalize my established skills while expanding my data science knowledge and tool box.
The capstone project was the most demanding aspect of the program. As such I most proud of the finale project. The project stretched each of us beyond the standard course work of the program and was quite satisfying.
To open doors so that I may further my research into the operational value of applying data science thought and practice to analytics of my domain.
Final Project: https://bengapple.shinyapps.io/coursera_nlp_capstone
Project Slide Deck: http://rpubs.com/bengapple/71376
A technologist, thinker, and tinkerer, Ivan facilitates the establishment of start-up companies by advising these companies about the hiring process, product development, and technology development, including big data, cloud computing, and cybersecurity. In his 17-year career, Ivan has held a wide range of engineering and management positions at various Silicon Valley companies. Ivan is a recent Wharton MBA graduate, and he previously earned his master’s degree in computer science from the Ensimag, and his master’s degree in electrical engineering from Université Joseph Fourier, both located in France.
****Why did you take the JHU Data Science Specialization?****
There are three reasons why I decided to enroll in the JHU Data Science Specialization. First, fresh from college, my formal education was best suited for scaling up the Internet’s infrastructure. However, because every firm in every industry now creates products and services from analyses of data, I challenged myself to learn about Internet-scale datasets. Second, I am a big supporter of MOOCs. I do not believe that MOOCs should replace traditional education; however, I do believe that MOOCs and traditional education will eventually coexist in the same way that open-source and closed-source software does (read my blog post for more information on this topic: http://ivantur.es/16PHild). Third, the Johns Hopkins University brand certainly motivated me to choose their program. With a great name comes a great curriculum and fantastic professors, right?
Once I had completed the program, I was not disappointed at all. I had read a blog post that explained that the JHU Data Science Specialization was only a start to learning about data science. I certainly agree, but I would add that this program is a great start, because the curriculum emphasizes information that is crucial, while providing additional resources to those who wish to deepen their understanding of data science. My thanks to Professors Caffo, Leek, and Peng; the TAs, and Coursera for building and delivering this track!
****What are you most proud of doing as part of the JHU Data Science Specialization?****
The capstone project made for a very rich and exhilarating learning experience, and was my favorite course in the specialization. Because I did not have prior knowledge in natural language processing (NLP), I had to conduct a fair amount of research. However, the program’s minimal-guidance approach mimicked a real-world environment, and gave me the opportunity to leverage my experience with developing code and designing products to get the most out of the skillset taught in the track. The result was that I created a data product that implemented state-of-the-art NLP algorithms using what I think are the best technologies (i.e., C++, JavaScript, R, Ruby, and SQL), given the choices that I had made. Bringing everything together is what made me the most proud. Additionally, my product capabilities are a far cry from IBM’s Watson, but while I am well versed in supercomputer hardware, this track helped me to gain a much deeper appreciation of Watson’s AI.
Thanks to the broad skillset that the specialization covered, I feel confident wearing a data science hat. The concepts and tools covered in this program helped me to better understand the concerns that data scientists have and the challenges they face. From a business standpoint, I am also better equipped to identify the opportunities that lie ahead.
Final Project: https://paspeur.shinyapps.io/wordmaster-io/
Project Slide Deck: http://rpubs.com/paspeur/wordmaster-io
Oscar is an assistant researcher at a research institute in a developing country, graduated as a licentiate in biochemistry and microbiology in 2010 from the same university which hosts the institute. He has always loved technology, programming and statistics and has engaged in self learning of these subjects from an early age, finally using his abilities in the health-related research in which he has been involved since 2008. He is now working on the design, execution and analysis of various research projects, consulting for other researchers and students, and is looking forward to develop his academic career in biostatistics.
I wanted to integrate my R experience into a more comprehensive data analysis workflow, which is exactly what this specialization offers. This was in line with the objectives of my position at the research institute in which I work, so I presented a study plan to my supervisor and she approved it. I also wanted to engage in an activity which enabled me to document my abilities in a verifiable way, and a Coursera Specialization seemed like a good option.
Additionally, I’ve followed the JHSPH group’s courses since the first offering of Mathematical Biostatistics Bootcamp in November 2012. They have proved the standards and quality of education at their institution, and it was not something to let go by.
I’m not one to usually interact with other students, and certainly didn’t do it during most of the specialization courses, but I decided to try out the fora on the Capstone project. It was wonderful; sharing ideas with, and receiving criticism form, my peers provided a very complete learning experience. After all, my contributions ended being appreciated by the community and a few posts stating it were very rewarding. This re-kindled my passion for teaching, and I’ll try to engage in it more from now on.
First, I’ll file it with HR at my workplace, since our research projects payed for the specialization
I plan to use the certificate as a credential for data analysis with R when it is relevant. For example, I’ve been interested in offering an R workshop for life sciences students and researchers at my University, and this certificate (and the projects I prepared during the specialization) could help me show I have a working knowledge on the subject.
Final Project: https://odeleon.shinyapps.io/ngram/
Project Slide Deck: http://rpubs.com/chemman/n-gram
I am passionate about turning raw data into actionable insights that solve relevant business problems. I also greatly enjoy leading large, multi-functional projects with impact in areas pertaining to machine and/or sensor data. I have a Mechanical Engineering Degree and an MBA, in addition to a wide range of Data Science (IT/Coding) skills.
I was looking to gain additional exposure into Data Science as a current practitioner, and thought this would be a great program.
I am most proud of completing all courses with distinction (top of peers). Also, I’m proud to have achieved full points on my Capstone project having no prior experience in Natural Language Processing.
I am going to add this to my Resume and LinkedIn Profile. I will use it to solidify my credibility as a data science practitioner of value.
Final Project: https://hedbergjeffm.shinyapps.io/Next_Word_Prediction/
Project Slide Deck: https://rpubs.com/jhedbergfd3s/74960
I was born in Argentina but now I’m settled in Spain. I’ve been working in computer technology since the eighties, in digital networks, programming, consulting, project management. Now, as CTO in a software company, I lead a small team of programmers developing a supply chain management app.
In my opinion the curriculum is carefully designed with a nice balance between theory and practice. The JHU authoring and the teachers’ widely known prestige ensure the content quality. The ability to choose the learning pace, one per month in my case, fits everyone’s schedule.
The capstone definitely. It resulted in a fresh and interesting challenge. I sweat a lot, learned much more and in the end had a lot of fun.
While for the time being I don’t have any specific plan for the certificate, it’s a beautiful reward for the effort done.
Final Project: https://herchu.shinyapps.io/shinytextpredict/
Project Slide Deck: http://rpubs.com/herchu1/shinytextprediction
I’m a 36 year old South African male born and raised. I recently (4 years now) immigrated to lovely Melbourne, Australia. I wrapped up a BSc (Hons) Computer Science with specialization in Computer Systems back in 2001. Next I co-found a small boutique Software Development house operating from South Africa. I wrapped my MBA, from Melbourne Business School, in 2013 and now I consult for my small boutique Software Development house and 2 (very) small internet start-ups.
One of the core subjects in my MBA was Data Analysis, basically an MBA take on undergrad Statistics with focus on application over theory (not that there was any shortage of theory). Waiting in a lobby room some 6 months later I was paging through the financial section of business focused weekly. I came across an article explaining how a Melbourne local applied a language called R to solve a grammatically and statistically challenging issue. The rest, as they say, is history.
I’m quite proud of both my Developing Data Products and Capstone projects, but for me these tangible outputs merely served as a vehicle to better understand a different way of thinking about data. I’ve spend most of my Software Development life dealing with one form or the other form of RDBS (Relational Database Management System). This, in my experience, leads to a very set oriented way of thinking about data.
I’m most proud of developing a new tool in my “Skills Toolbox” that I consider highly complementary to both my Software and Business outlook on projects.
Honestly, I had not planned on using my Certificate in and of itself. The skills I’ve acquired has already helped shape my thinking in designing an in-house web based consulting collaboration platform.
I do not foresee this being the last time I’ll be applying Data Science thinking moving forward on my journey.
Final Project: https://schonken.shinyapps.io/WordPredictor
Project Slide Deck: http://rpubs.com/schonken/sentence-builder
David is passionate about solving the world’s most important and challenging problems. His expertise spans chemical/biomedical engineering, regenerative medicine, healthcare technology management, information technology/security, and data science/analysis. David earned his Ph.D. in Chemical Engineering from Northwestern University and B.S. in Chemical Engineering from the University of Notre Dame.
I enrolled in this specialization in order to advance my statistics, programming, and data analysis skills. I was interested in taking a series of courses that covered the entire data science pipeline. I believe that these skills will be critical for success in the future.
I am most proud of the R programming and modeling skills that I developed throughout this specialization. Previously, I had no experience with R. Now, I can effectively manage complex data sets, perform statistical analyses, build prediction models, create publication-quality figures, and deploy web applications.
I look forward to utilizing these skills in future research projects. Furthermore, I plan to take additional courses in data science, machine learning, and bioinformatics.
Final Project: http://dt444.shinyapps.io/next-word-predict
Project Slide Deck: http://rpubs.com/dt444/next-word-predict
I’m a financial journalist from Singapore. I did philosophy and computer science at the University of Chicago, and I’m keen on picking up more machine learning and data viz skills.
I wanted to keep up with coding, while learning new tools and techniques for wrangling and analyzing data that I could potentially apply to my job. Plus, it sounded fun.
Building a word prediction app pretty much from scratch (with a truckload of forum reading). The capstone project seemed insurmountable initially and ate up all my weekends, but getting the app to work passably was worth it.
It’ll go on my CV, but I think it’s more important to be able to actually do useful things. I’m keeping an eye out for more practical opportunities to apply and sharpen what I’ve learnt.
Final Project: https://melissatan.shinyapps.io/word_psychic/
Project Slide Deck: https://rpubs.com/melissatan/capstone
Felicia likes to dream, think and do. With over 20 years in the IT industry, her current fascination is at the intersection of people, information and decision-making. Ever inquisitive, she has acquired an expertise in subjects as diverse as coding to cookery to costume making to cosmetics chemistry. It’s not apparent that there is anything she can’t learn to do, apart from housework. Felicia lives in Wellington, New Zealand with her husband, two children and two cats.
Well, I love learning and the JHU Data Science Specialization appealed to my thirst for a new challenge. I’m really interested in how we can use data to help people make better decisions. There’s so much data out there these days that it is easy to be overwhelmed by it all. Data visualisation was at the heart of my motivation when starting out. As I got into the nitty gritty of the course, I really began to see the power of making data accessible and appealing to the data-agnostic world. There’s so much potential for data science thinking in my professional work.
Getting through it for starters while also working and looking after two children. Seriously though, being able to say I know what ‘practical machine learning’ is all about. Before I started the course, I had limited knowledge of statistics, let alone knowing how to apply them in a machine learning context. I was thrilled to be able to use what I learned to test a cool game concept in my final project.
I want to use what I have learned in as many ways possible. Firstly, I see opportunities to apply my skills to my day-to-day work in information technology. Secondly, I would like to help organisations that don’t have the skills or expertise in-house to apply data science thinking to help their decision making and communication. Thirdly, it would be cool one day to have my own company consulting on data science. I’ve more work to do to get there though!
Final Project: https://micasagroup.shinyapps.io/nwpgame/
Project Slide Deck: https://rpubs.com/MicasaGroup/74788