- 8:00am - 8:30am - Welcome
- 8:30 - 9:00am: - Introduction - Organizer and Sponsor
- 9:00am – 10:15am: - Workshop 1: Big Data – Application in business
- 10:15am – 11:45am: - Workshop 2: AI - Opportunities and challenges for Vietnamese businesses
- 11:45am – 12:00pm: Talkshow AI and Big Data with Technology Specialist
2.2 Details of each workshop:
2.2.1 Workshop 1: Big Data - Application in business
1. What is Big Data?
- Why data is big in systems?
- What are data sources?
- Questions to open discussion?
2. What are business requirements?
- QC testing
- Data Analytic
3. Problems with current storage and processing?
- Limitations in relational database
- Resolve a case in relational DB
4. Systems design for business grow
- Business goals
- Design a system for Fin-tech
- Why for the design
5. Business Cases
- Case 1: Make historical reports
- Case 2: Cohort in Marketing
- Case 3: User Behavior in App
- More open cases: Fraud, Detect User ID
6. Discussion and questions
- Introduction to Machine Learning
- The algorithms & methods apply of Machine Learning
- Workshop: Recommendation problem for users
- Deep learning & Deep Learning applications
- Workshop Deep Learning
- Q & A
3.1 Huynh Van Phuong
Workplace: VNG Joint Stock Company
Experience: 11 years
3.2 Dang Anh Toan
Workplace: NashTech Global Company
Experience: 20 years
- Main participants: Strategic traders, consultants, technical managers who want to apply AI and Big Data into their business.
- AUDIENCE - Expert ITs, - Testers, - Developers, - Trainers, - Trainees, - Lecturers - Managers - CTO
AI was born in 1956. John McCarthy was called the father of AI who founded the first AI team. AI is constantly evolving and exploding despite its ups and downs for a long time. By 2012, AlexNet was born that smashed the icy winter of AI. Accompanied by the development of the digital era, the data also exploded along. Older algorithms and technologies no longer respond to large data, unstructured data like images, natural language, etc. Therefore, DL algorithms are constantly being developed and optimized for the use of large data sources as well as extremely complex calculations.
First of all, the speech recognition technologies have been greatly improved. People can use voice to control smart devices such as TVs, smartphones; Virtual assistants such as Siri, Cortana, and Alexa are available in almost Google products. The next is the automatic translation and natural language processing technologies increasingly superior; the breakthrough of DL in image recognition in medicine helps diagnose the disease through X-ray images, MRI is more accurate than the therapist. And then the unmanned vehicles are on trial day on the roads in Europe and America.
In addition, we must mention the robot and IOT products before the breakthrough in DL. The problem is still controversial so far is whether computers and robots have invaded and controlled humans?
AI machines have been everywhere. They can be powerful helpers, the eyes of the blind to be able to recognize things and describe them. These machines can hear people, look around to perform high-precision tasks, or they can rely on human gestures to perform corresponding actions.
Outstanding achievements like AlphaGo have applied Reinforcement Learning to winning people in most games, especially Go, a kind of complicated game with huge steps. Standford applied DL to detect skin cancer at a higher rate than dermatologists; detect heart problems with a thousand times more accuracy and faster than specialists. The Tesla, Uber, Alphabet Waymo self-driven programs have a 40 times lower incidence of traffic accidents than humans. A guarded robot with thermal and motion sensors can identify suspicious targets from a distance of 2 miles,…
It can be seen that AI is present everywhere, in everything from health, life,… to the fields of industry, agriculture, defense ... It can be said this is the era and the industrial revolution 4.0. How do these wonderful software, machines do that?
Big Data: Introduction:
With the explosive growth of technology leading to increased data volumes, the old technique does not meet the needs of storage, retrieval, synthesis and analysis. This workshop highlights issues encountered with conventional data techniques as well as in building storage systems and processing Big Data. In addition, it also adds security and BI tools to the listener to get more ideas in building the perfect Big Data system.