AGENDA - BIG DATA HACKATHON 2018
AGENDA:
1st DAY - FRIDAY, 29 JUNEVENUE: ADA University, Building B (Majlis room, Books & Bytes)
09:00 Registration of Teams 10.00 Opening and Welcome Session (from Organizers and Supporting Partners) 10:30 Introduction to Hackathon Program and Logistics 10:50 Jury Members Introduction, Hackathon Criteria and Rules 11:00 Coffee Break 11.30 Announcement of Tasks, Data Manifesto, Data Access Credentials 12.00 Hackathon Kicks Off! 14:00 Lunch Hackathon Continues… 19:00 Dinner (pizza) Hackathon Continues over Night…2nd DAY - SATURDAY, 30 JUNE
VENUE: ADA University, Building B (Books & Bytes, Majlis room)
09.00 Hackathon Continues... 12:00 Hacking Ends 12.00 Presentations by Teams (5 minutes each + 3 minutes Q&A) 13:00 Lunch 13.30 Presentations by Teams (5 minutes each + 3 minutes Q&A) 14.30 Judging by Jury 15:30 Awards & Closing Ceremony 16.00 Hackathon is over!
DESCRIPTION / PURPOSE:
Nothing ever becomes real till it is experienced. - John Keats
We are presenting the first Data-related Hackathon in Azerbaijan, where you are expected to demonstrate your technical capabilities tackling with Data. Mission of Hackathon is to reveal hidden opportunities that Technology and Data provides to you turning raw Data into actionable intelligence. The primary purpose of of Data Analytics Hackathon is to bring together the data scientists, business analysts, software developers, visualisation specialists and simply people with data sense from academia, business and public who will be asked to solve real Industry-related problems using Analytics Techniques and Machine Learning applied to the real data provided by industries. The Data Analytics Hackathon is 24 hours non-stop hackathon with large IT & Technology Community engagement will be held at ADA University in the haart of Baku city.PARTNER SPONSORS/ORGANIZERS
- PASHA Bank OJSC - Sponsor and Partner
- ASAN Service - Partner
HOSTS AND COORDINATORS:
- ADA Center for Data Analytics Research (CeDAR)
- IEEE Azerbaijan Chapter
- Azerbaijan ACM Chapter
- ADA Innovation Center
HACKATHON PRIZES:
1) Task from Banking Sector
- 1st Place Winner - 3000 AZN
- 2nd Place Winner - Smart Watches
- 3rd Place Winner - Computer Bags with Accessories
2) Task from Public Sector
- 1st Place Winner - 500 AZN
- 2nd Place Winner - 300 AZN
- 3rd Place Winner - 200 AZN
HOW TO REGISTER FOR PARTICIPATION?:
The registration for Big Data Hackathon is available at the offical website of BIG DATA HACKATHONWHO CAN PARTICIPATE?
Participation is open to all: students, researches, developers, industry professionals, etc., everybody who feel passionate about working with Data.WHY SHOULD I PARTICIPATE? (BENEFITS)
- Try new technology, learn and compete in friendly and collaborative environment
- Participate in dedicated training provided by Center for Data Analytics Research (CeDAR)
- Networking with peers and industry experts
- Visibility to industry increasing chances for internship and full-time position
- Learn and face with real cross-industry business challenges
HOW TO FORM A TEAM?
- Max number of team-members is 4;
- Each individual must be a member of just one team;
- Teams should be formed before the Hackathon during registration process;
- Individual participation is allowed, but TEAMs will have much higher chance to participate.
RECOMMENDED QUALIFICATIONS:
- Experience in statistics and statistical tools
- Experience in Machine Learning and Data Science methods to business problems
- Programming experience in any of: R, Python, Scala, SQL
- BSc / MSc / PhD in the field of Computer Science, Applied Mathematics, or any other area of STEM
- Strong presentation and communication skills
- Team work and project management skills
PARTICIPATION COST:
Participation is free-of-chargeTRAININGS:
Training of following topics will be organized for Hackathon participants:- Data Manipulation and Analytics with R and Python
- Machine Learning Algorithms and Methods
Training Experts:
- Dr. Abzetdin Adamov, Director, Center for Data Analytics Research (CeDAR), ADA University
- Dr. Samir Rustamov, Assistant Professor, School of IT & Engineering, ADA University
Topics to be Covered:
- Introduction to Big Data Analytics
- Data Manipulation and Processing with R and Python
- Data Statistical Analysis with R
- Data Visualization with R
- Essentials of Machine Learning with R and Python
TIMING:
Starts at: Fri June 29 2018 12:00:00 GMT+0400 (AZT)Closes on: Sut June 30 2018 12:00:00 GMT+0400 (AZT)
FINAL SUBMISSION:
Final submission of solution with source code is compulsory. Details will be provided later.HACKATHON RULES:
- All teams/participants must start hacking at the same time. The work done before start is not acceptable;
- Submissions done after Hackathon closed will not be considered;
- Using any Data beyond provided is not allowed;
- The business problem (case) and related Data will be released at the start of Hackathon;
- Each participant can be a member of only one team;
- You are free to use any technique, tool and machine you have access to;
- You are free to use any programming language or statistical software;
- Each team of individuals is expected to rely just on own knowledge and experience. Support from outside is not allowed;
- Any participant can be disqualified if he acts fraudulently.
DELIVERABLES:
Following are the deliverables expected from each team at the end of contest (to be sent to JUDGES email address): Codes (in R, Python, etc.) for Data Manipulation (if applicable) and Model (please add comments as appropriate for adequate understanding of the code and each step used solution)JUDGING CRITERIA:
All criteria are equally weighted of 1/3. Final presentations will be evaluated by each of three criteria on a 1 – 5 scale:- Technical Approach - How technically sophisticated, advanced, practical and useful the approach to solve a problem with Data?
- Innovativeness - How unique, novel and creative the idea? Did the team positively surprise you with their methods? Is the approach is practically applicable and useful in real life?
- Presentation Quality - How well team introduced their approach and solution. Is the project easily understandable? Is a person from the field able to understand the insights? How well-defined are the insights?
JUDGES:
- Dr. Abzetdin Adamov, Director, Center for Data Analytics Research (CeDAR), ADA University
- Dr. Samir Rustamov, Assistant Professor, School of IT & Engineering, ADA University
- Mr. Kamal Fataliyev, Lead Developer / Co-founder, Coderoo Digital Agency, Sydney (Australia)
- Mr. Ramin Orucov, Technical Director, ITCITY
- Mr. Shahmeddin Abdullayev, Head of Database Administration & Business Intelligence, PASHA Bank
- Mr. Nail Ismayılov, Data Analytics Team Leader, ASAN Services
HELPFUL TOOLS:
See the list of most popular resources, APIs, libraries, tools, and ideas that can help you:- R Programming Language: R Interpreter, R Studio
- Python Programming Language Python Interpreter
- Anaconda Distribution Spyder (Python IDE) and many other tools and packages...
- Github Pages Powerful Software Development Platform
- Google Slides Google Slides
- Microsoft PowerPoint
- Fire Sharing - Dropbox, Google Drive
- Text/Code Editors - Notepad++, TextWrangler