Deep Learning, Machine Learning, Data Science, Web Engineering and more.
  • Designed to gradually learn core Deep Learning technology
  • Course content:
    • Machine learning
    • Neural network, MLP and Optimizers
    • Autoencoders
    • Convolutional neural networks (CNNs)
    • Generative Models (VAE and GAN)
    • NLP, Recurrent neural networks and LSTMs
  • Textbook: “deep learning” (machine learning professional series)
  • Number of lectures: 12
  • Onsite courses;
    • Deep Learning Core 2015, 2016 (Voluntary Lectures)
    • Advanced Artificial Intelligence I 2016 (The University of Tokyo)
  • Designed to acquire more practical research and development skills for those who already have basic knowledge of Deep Learning
  • Course content:
    • advanced image processing
    • Large-scale computing; database and GPU
    • deep Q-networks (DQNs) and reinforcement learning
    • Project and team development
  • A project-oriented class
  • textbook: “deep learning” (machine learning professional series)
  • number of lectures: 12
  • Onsite courses;
    • Advanced Artificial Intelligence II 2016 (The University of Tokyo)


  • Designed to train Chief Marketing Officers (CMOs) that can demonstrate high consumer intelligence on a global scale to run business
  • Course content:
    • Marketing theory
    • Basics of machine learning
    • Basics of data science
  • textbook: TBA
  • number of lectures: 13
  • Onsite courses;
    • Global Consumer Intelligence 2016 (The University of Tokyo)

TBA – Linux, SSH, Package management, Server configuration, Terminal multiplexers, Virtualization,  etc.


TBA – HTTP and other protocols, Databases, Package management, Web frameworks, Agile development, Git(hub), Scrum, DevOps, Test, Teamwork,