The New Brunswick Libraries’ Quantiative Data Analytics Graduate Specialist, Hang Miao, will be offering a three-part series of Python workshops in October, starting Friday October 5.
Note: additional more advanced workshops for November will be announced later in October.
☞ RSVP for the Python workshops.
Workshops are offered in either Alexander Library or LSM (with identical content). Participants in LSM-based workshops must bring their own laptops. At Alexander, you can either bring your own laptop, or use the desktops in the lab.
Python Basics and Data Exploration
October 5, 1-3 pm, Alexander Library Room 413
October 10, 3:30-5:30 pm, Library of Science and Medicine Electronic Classroom (3rd floor)
This workshop will be an accelerated introduction to fundamental concepts such as variable assignment, data types, basic calculations, working with strings and lists, control structures (e.g. for-loops), functions. We will also start working with pandas, a popular data science library in Python, to explore a dataset on foodborne outbreaks reported to the CDC.
Data Manipulation and Analysis
October 12, 1-3 pm, Alexander Library Room 413
October 17, 3:30-5:30 pm, Library of Science and Medicine Conference Room (1st Floor)
In this workshop, we will dive into the world of arrays and data frames using the NumPy and pandas libraries. We’ll cover data cleaning and pre-processing, joining and merging, group operations, and more. If you work with tabular data, this workshop is for you!
Data Visualization and Machine Learning
October 19, 1-3 pm, Alexander Library Room 413
October 24, 3:30-5:30 pm, Library of Science and Medicine Conference Room (1st floor)
Interested in finding patterns and predicting unknown attribute values in your data? Join us for an overview of machine learning techniques implemented using the scikit-learn library. We’ll also learn how to do data visualization with matplotlib, a popular plotting library in Python.
Open Follow-up Session on Python
October 26, 1-3 pm, Alexander Library Room 413
October 31 3:30-5:30 pm, Library of Science and Medicine Electronic Classroom (3rd floor)
This open session allows participants to bring their questions or issues from previous sessions to practice and further develop skills.
I was delighted to be invited to return to Mongolia again for a more in-depth visit to the Mongolian University of Life Sciences [Хөдөө Аж Ахуйн Их Сургууль]. I was honored by the invitation from the Dean of the School of Economics and Business [Эдийн засаг бизнесийн сургууль], B. Baasansukh, and P. Munkhtuya, Chair of the Department of Economic Statistics and Mathematical Modeling, to come and teach a one week Short Course on Applied Multivariate Statistical Methods with R [Олон хэмжээст статистикийн богино хэмжээний сургалт R программ дээр]. This post is a brief summary of my trip.
I got to Ulaanbaatar on my first ever flight on MIAT Mongolian Airlines, which was quite comfortable.
On Monday, February 26, we jumped right into work. The material for the short course was adapted from the book and associated R code by Brian Everitt and Torsten Hothorn, An Introduction to Applied Multivariate Statistical Analysis with R, Springer, 2011. The eight chapters of the book were covered in four days. Topics covered were the following:
- R environment, setup, basics
- Multivariate Analysis – what is it?
- Data Exploration and Visualization
- Principal Components
- Multidimensional Scaling
- Exploratory Factor Analysis
- Confirmatory Factor Analysis
- Structural Equation Modeling
- Cluster Analysis
- Repeated Measures
The Everitt and Hothorn text was particularly useful for its compact treatment of complex topics, and the self-contained nature of the included R code demo modules.
There were a total of 31 participants attending, although course and meeting conflicts prevented some from coming every day. The MULS School of Economics and Business had 20 participants, with the remaining attendees coming from the Division of Science and Research, the School of Agroecology, the School of Veterinary Medicine, and the School of Engineering and Technology. Outside of MULS, participants also came from the National Statistics Office of Mongolia and the Cabinet Secretariat of the Government of Mongolia.
All participants followed along by executing sample code on their own laptops. All presentation materials and code are available from https://github.com/ryandata/multivariate. Supplemental texts and files were made available using a portable PirateBox to distribute materials via local wireless network. See this post on how to set up a PirateBox.
The interaction was lively and particularly aided by assistance in translation from G. Bilguun, O. Amartuvshin, and T. Suvdmaa. I hope the participants enjoyed it as much as I did!
Putting our knowledge of R to immediate use, we used R to select a random sample of winners of swag provided by Rutgers’ Master of Business and Science program.
During the week, I also had the opportunity for several meetings to discuss future collaborations on projects to improve the academic and data infrastructure of MULS, which I believe will be the subject of future collaborations. The week also included some delicious food, including a hot pot dinner and khorkhog [хopxoг] and khuushuur [хуушууp].
On Thursday afternoon, I had the opportunity to address a group of undergraduate statistics majors on trends in data science and its intersection with statistics. I argued that the expansion in the power and availability of open source software and data has made it possible for anyone, from Mongolia or even the United States (where there are arguably more distractions) to study and master the tools and skills that underpin the most dynamic growth sectors for future jobs.
Finally on Friday, we wrapped up the course with some final discussion and the presentation of certificates to participants.
Mongolia is always a land of warm welcome and surprises. Thanks to my hosts at SEB-MULS for a fantastic trip, filled with learning. Thanks to D Music for inspiration as always. And thanks especially to P. Munkhtuya for leading all of the organizational efforts for my visit. I am looking forward to working together with MULS colleagues in the future! Маш их баярлалаа!
While it is the subject for another blog post or another blog, Mongol culture has long held my fascination. Thanks to a series of fortunate events, I had the opportunity to bring some of my favorite interests (data, statistics, R, Mongolian) all together to form an unforgettable experience in May 2017. During one week in Ulaanbaatar, I visited three of the oldest, largest, and most important Mongolian universities, as well as the nerve center of Mongolian data, the National Statistics Office.
National Statistics Office of Mongolia
The first and most intensive event was my invitation to present two days of workshops on Data Science at the National Statistics Office of Mongolia (Монгол Улсын Үндэсний статистикийн хороо). On May 8 and May 9, I delivered all-day presentations and interactive training on Data Visualization, Big Data, Reproducible Research, and Data Literacy. The presentation slides in English and accompanying Mongolian translation are available here.
We covered lots of ground, and I was also able to learn about the data environment in Mongolia and some of NSO’s data dissemination efforts such as the 1212.mn data portal. The facilities at NSO were superb, and the audience of 33, consisting primarily of government data professionals from the NSO and other Mongolian agencies were an outstanding group. It was truly a privilege to be able to work with them. An article (in Mongolian) about the event is here.
In particular, I would like to thank Ch. Davaasuren (Research and Development Director of the Mongolian Marketing Consulting Group for arranging the event, to L. Myagmarsuren (Director of Information Technology at NSO) for hosting it, and to A. Ariunzaya (Chair of NSO) for the invitation.
These three can be seen at the opening of the event [at the link below], along with me and my poor Mongolian – уучлаарай (sorry!). I promise it will improve!
The event was greatly enriched by sponsorship from IASSIST, the International Association for Social Science Information Services and Technology. IASSIST is developing outreach efforts to areas around the world, and provided translation services and lunch for workshop participants. We had two days of delicious хуушуур (huushur), сүүтэй цай (milk tea), and other Mongolian specialties at Modern Nomads. Joining IASSIST is a great way to get in touch with a worldwide network of data professionals!
National University of Mongolia
On Wednesday, May 9, I spoke on Data Literacy to approximately 70 students of statistics at the National University of Mongolia (Монгол Улсын Их Сургууль). Even though the talk started at 7:40 am, students were attentive and asked probing questions. Clearly, they are the future of data science –very curious about career trends and the nature of the work and skills required. I am sure they will succeed if they remain as focused as they were that day! Амжилт хүсьё!
Thanks to D. Amarjargal for inviting me, and B. Myagmarsuren for translating!
Mongolian University of Life Sciences
On Thursday, May 10, I traveled to the southern side of Ulaanbaatar to speak at the Mongolian University of Life Sciences (Хөдөө Аж Ахуйн Их Сургууль), giving two presentations on Big Data and Data Visualization to a group of approximately 20 faculty of the School of Economics and Business.
The faculty here were very welcoming and discussed many issues in applying big data and visualization techniques to their work. Many thanks to P. Munktuhya (Head of the Department of Economics, Statistics, and Mathematical Modeling) for arranging the event, to G. Ganzorig (Senior Lecturer in Agricultural and Applied Economics) for translation, and to B. Baasansukh (Dean of the School of Economics and Business) for the invitation.
I was also able to have a very informative and positive meeting with Ts. Sukhtulga (Chief of Administration and International Affairs) to discuss possibilities for cooperation with Rutgers University. An article (in Mongolian) about my visit appeared here. I really regretted not having more time to spend here!
Mongolian University of Science and Technology
My final talk on Friday, May 11 was at the Mongolian University of Science and Technology (Шинжлэх Ухаан, Технологийн Их Сургууль), where I spoke on Big Data, Reproducible Research, and Data Visualization, hitting highlights from my earlier presentations during the week.
Approximately 40 faculty and students from MUST’s School of Business Administration and Humanities attended. Once again, the audience was attentive and questioning up until the end, even though the talk was held late on Friday afternoon. I was very impressed by the curiosity and dedication of the Mongolian academic community here, and throughout my trip.
At MUST, I would like to thank J. Oyuntungalag (Professor of Technology Management) for arranging the talk. I also enjoyed a good meeting with U. Batbaatar and P. Jargaltuya of the Office of International Affairs and Cooperation.
On Friday, I was also able to spend some time at the Mongolian Marketing Consulting Group‘s offices to learn more about how they conduct polling, market research, and other data collection, thanks to the hospitality of Ch. Davaasuren.
It was such a memorable and rewarding experience that I must continue to thank those who made it possible, once again Ch. Davaasuren who helped throughout the week, and especially to M. Bayarmaa who worked tirelessly to organize many aspects of the week’s events and behind the scenes to keep things running smoothly.
I can only hope that this is the start of a long and productive collaboration with the Mongolian data world.
Би цагийг гайхалтай сайхан өнгөрөөсөн! (I had a glorious time!)
I am delighted to announce that I have been invited to present on several data science topics at the Mongolian National Statistics Office (Монгол Улсын Үндэсний Статистикийн Хороо) and the National University of Mongolia (Монгол Улсын Их Сургууль) from May 8th to 10th.
I will post more detailed commentary after the visit, but I am excited by the opportunity to meet colleagues and learn about the Mongolian environment, and explore the potential for collaboration on data issues.