What You Will Create
10-Week Bootcamp

In this course, students will get to learn basics of machine learning, deep learning, and their cool applications such as handwritten recognition and machine translation. The course is designed for Vietnamese students (taught in Vietnamese with English terminologies) and split into two parts. In the first part, we will cover some foundations in maths (linear algebra, probability) as well as basic Python and NumPy to quickly get students up to speed; then we teach basics of machine learning, deep learning, and TensorFlow - Google's most popular deep learning framework. The second part focuses on Natural Language Processing in which students will get to build a real-world machine translation system using the currently most successful approach - sequence-to-sequence models. Students will have a chance to apply new knowledge to problems of their own interest for the final project. Our goal is to provide a solid background and practical experience for students to tackle new problems with machine learning after taking the course.

Apply by 01/03/2019
  • Week 1

    Course introduction. Mathematics review (Linear Algebra, Probability and Calculus).
    Introduction to Python and NumPy libraries.

    Exercise: Use Python to solve simple problems. Use Numpy to execute simple computations.
    Lab: Install and use TensorFlow with GPU on Google Cloud Platform.

  • Week 2

    Introducing Softmax Regression to solve multi-class classification problem and its relationship to Logistic Regression.
    Introduction to Tensorflow.
    Linear Regression to predict real­valued outputs.

    Exercise: Use Tensorflow to execute simple computations. Use Linear Regression to predict house prices.

  • Week 3

    Logistic Regression to solve binary classification problem.
    Gradient Descent to learn parameters in models.
    Softmax Regression to solve multi­class classification problem.

    Assignment 1 (20%): Using Logistic Regression to recognize Vietnamese motorbikes. Using Softmax Regression to solve handwriting recognition problem.

  • Week 4

    Introduction to Neural Networks.
    Backpropagtion algorithm, stochastic gradient descent, and dropout.

    Assignment 1 (20%): Using Feedforward Neural Networks to improve handwriting recognition accuracy.

  • Week 5

    Introduction to Convolutional Neural Networks (CNNs) and commonly used architectures (AlexNet, VGGNet, InceptionNet, ResNet).

    Lab: Using CNNs to improve handwriting recognition accuracy.

  • Week 6

    Introduction to deep learning for natural language processing.
    Introduction to word embeddings.
    Introduction to Recurrent Neural Networks (RNNs) and language modeling.

    Midterm Quiz (10%)
    Assignment 3 (20%): Using RNNs to do sentiment analysis.

  • Week 7

    Revise RNNs and introduction to Long Short­Term Memory (LSTM).
    Introduction to sequence­to­sequence (seq2seq) models & their applications.

    Lab: Neural machine translation tutorial using seq2seq.
    Course project: discussion.

  • Week 8

    Introduction to Attention Mechanism for seq2seq.
    Advances of seq2seq models.

    Course project: discussion.

  • Week 9

    Guest Lectures.

    Course project: discussion.

  • Week 10

    Guest Lectures.
    Course Review.

    Course project (30%): presentation + report.

Our world-class
Kien Huynh
Kien is a research assistant at Ho Chi Minh city University of Technology. He has published several IEEE papers about applying deep learning and machine learning on vision-based traffic density estimation. Currently, he’s a PhD Student at Stony Brook University, NY. Kien received his Master degree in Computer Science in 2017 at HCMUT. As of 2018, Kien has a 4-year experience as a teaching assistant.
Phat Hoang
Phat is working as a Data Scientist at Techbase Vietnam (a subsidiary of Yahoo! Japan). He receives his Bachelor degree in Computer Science at University of Science - VNUHCM. In 2015, Phat did his internship at Japan Advanced Institute Science and Technology (JAIST). From August 2015 to March 2017, he worked as Research Engineer at Knorex to develop text mining tools in advertisement.
Chip Huyen
Chip Huyen is a writer and computer scientist. She’s worked with multiple tech companies in Vietnam, US, and Europe, including Netflix, Primer.ai, Coc Coc. She’s currently a master’s student at Stanford University, where she created and teaches the course TensorFlow for Deep Learning Research. Her work focuses on the intersection between Natural Language Processing and Deep Learning. She’s also the author of three bestselling Vietnamese books: “Xách ba lô lên và Đi” series and “Giấc mơ Mỹ – Đường đến Stanford”.
Vu Huu Tiep
Tiep is currently pursuing the Ph.D. degree with the information Processing and Algorithm Laboratory (iPAL), The Pennsylvania State University. His research interests are broadly in the areas of statistical learning for signal and image analysis, computer vision and pattern recognition for image classification, super-resolution, recovery and retrieval. He is the author of a Machine Learning blog in Vietnamese [machinelearningcoban.com] with more than 10k followers.
Thang Luong
Thang Luong is currently a research scientist at Google Brain, using deep learning to solve natural language problems. He obtained his PhD from Stanford University in which he built state-of-the-art neural machine translation systems at both Google and Stanford. Seeing the love and passion of Vietnamese students for AI, machine learning, and deep learning, he founded VietAI to bring back knowledge to Vietnam.
Our world-class
SaiGon Teaching Team
Thuyen Phan
Thuyen Phan is a fresh graduate from University of Science, VNU-HCM. He interned at Google US 2 years ago. Now, Thuyen Phan is a software engineer at Christina's. He is seeking new technologies and to solve new problems.
Thang Le
He graduated from HCMUT with first-class honor’s degree. He has a strong background in machine learning. Specifically, he got interested in probabilistic graphical models, natural language processing and some deep learning stuff. He is currently working at GraphicsMiner Lab on machine reading comprehension. In addition, some of his hobbies include playing football, listening classical music and travelling.
Duy Vu
Duy Vu is a Technical lead at GraphicsMiner Lab. Duy has experienced in developing wide range of software systems related to machine learning, big data and cloud computing technologies. In addition, his experiences in Pilot AI class as a teaching assistant would support VietAI classes. One more thing Duy has a strong passion in hiking and traveling with his bicycle.
Quynh Anh
Anh Nguyen: She is a VietAI Machine Learning (ML) class alumna. She actually majored in Chemical Engineering in college but decided to switch to Computer Science during her senior year. Anh became more interested in ML after taking one ML class with VietAI and is now wishing to join the teaching team in hopes of sharing what she has learned as well as connecting with other ML enthusiasts.
Chuong Huynh
Chương Huỳnh: He is a fresh graduate from University of Science, VNU-HCM with Honor’s degree. In VietAI first course, he is the valedictorian with absolute point. Chuong’s interested in medical image analysis, especially, his paper about CheXNet has just been accepted as long paper at KSE conference 2018. He’s now a product engineer at hasBrain, writing deep learning content as well as developing experiment tool in data science.
Giang Tran
Giang Tran is a software engineer at a financial startup in US name ThinkScale. He has strong passion about mathematical concept in Machine Learning. His interest research is Natural Language Processing. He's eager to learn and discover things every single day for his curious mind.
Hoa Nguyen
Nguyen Thanh Hoa majored in pharmacy and her interest in machine learning (ML) stemmed from the time when she was conducting her graduation project on computer-aided drug discovery. This brought her to the first ML class of VietAI where she was inspired by its fascinating lessons and interdisciplinary concepts. She is highly motivated to apply machine learning to leverage biomedical and healthcare data.
Cong Quoc
Quoc Pham is a Data Scientist at Zalo Group. He receives his Bachelor's degrees with Honours in Computer Science at University of Science. He has passion about deep learning and its theory. His research interest includes computer vision, natural language processing
Xanh Ho
She is a teaching assistant at the University of Science - Ho Chi Minh City. She receives her Bachelor degree in Computer Science. In 2017, Xanh did her internship at National Institute of Informatics (NII), Japan in 6 months. Her research interest is about natural language processing and machine learning.
Bao Tran
She is working as an NLP research scientist at Knorex - a provider of performance marketing technologies and solutions. She has completed her bachelor degree in Computer Engineering at Ho Chi Minh city University of Technology. In undergraduate years, she received the third prize in the national round of ACM/ICPC contest. Her research interests focus on Natural Language Processing and Machine Learning.
Bao Dai
Bao Dai is now working as a Natural Language Processing (NLP) research scientist at Knorex. He receives his Bachelor degree in Computer Science at University of Science ­ VNUHCM. He has published several scientific papers about applying neural networks to solve several tasks in NLP. His research interest also includes computer vision, deep learning and harmony in music theory
Our world-class
Hanoi Teaching Team
Do Truong
Quoc Truong Do received his B.E. from University of Engineering and Technology, Hanoi, Vietnam, in 2013, his M.S. and Ph.D. from the Graduate School of Information Science, NAIST, Nara, Japan in 2015 and 2018. He is currently the CTO of Vietnamese Artificial Intelligence System company and also a research scientist at ICTLab of the USTH university. He interested in speech and natural language processing, with a focus on speech recognition, and speech translation.
Nguyen Binh
He graduated from Hanoi University of Science and Technology in Information System with impressive project about OCR in smartphone. Currently, he is working as a Machine Learning Engineer at Samsung where his projects specialize in Recommendation System, Search Engine and other NLP problems. He published an Vietnamese spell correction application using seq2seq model under the name “Botdy”.
Nguyen Ba Ngoc
He is Community Manager of GDG Hanoi with mission to connect developers who are interested in Google technologies. He loves programming and machine learning and he strongly believes “Machines are capable of getting past the limits of human speed”. He won Singapore UNESCO Open Data and Science Hackathon 2018. He has been writing blog “Learn machine learning in two months” and got 560 stars on Github. This year, he’s with his friends published an Google I/O Extended Hanoi App and it was rapidly featured as top 1 under event category in Google Play.
Le Minh Hoa
Hoa is a Data Scientist at NextSmarty-a Hanoi-based startup which provide on-premise solutions for personalized recommendation service. He completed a BSc in Mathematics with Finance at Exeter University and a MPhil in Computational Biology at Cambridge University, before reading Statistical Machine Learning at Data Science Lab, HUST as a Research Assistant. Since then he has been pursuing AI/Machine learning with keen interests in generative models and their inspiring applications. By joining VietAI, he hopes he can better conveys the joy of the field, and help the other aspiring learners through the challenging journey ahead.
Son Lam Ho
He has a PhD in mathematics at University of MaryLand. Currently he is the lead data scientist at PropertyPricetag Sdn Bhd (Malaysia). He has taught courses in mathematics and statistics as a graduate assistant at University of Maryland, and as a postdoctoral researcher at University of Luxembourg and University of Sherbrooke. He would like to help Vietnamese students along their journey in data science and machine learning.

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