Faculty at School of Computer Science, IDC Herzliya; a decade of experience teaching scientific Python in Academia and Industry.
Software developers and engineers interested in a pratctial introduction to deep learning.
An introduction to data processing, analysis, and visualization with Python combined with a primer in deep learning with neural networks.
2-3 days, 16-24 hours of interactive face-to-face sessions or Zoom webinar.
Instruction with code. Built-in exercises and problems. Laptops open with source code throughout all sesssions. Homework assignments for deep recitation.
Coding in Python, inside interactive Jupyter notebooks, using Keras, a popular deep learning library.
Understanding the math behind neural networks using Python and its scientific stack.
Training and using neural networks using Python, TensorFlow, and Keras.
Experience in software development (not necessarily Python) and a basic understanding of statistics, linear algebra, and calculus (BSc in exact sciences or similar).
Install the Anaconda with Python 3 Distribution for free.
Do some preliminary reading (2-3 hours) and exercises (3-4 hours after each day) at home or the office.
I'm a Faculty member of the School of Computer Science at IDC Herzliya. I was a postdoctoral fellow at Stanford University and earned my PhD in Mathematical & Computational Biology from Tel Aviv University. I've been teaching Python in Academia and Industry since 2011, including at Tel Aviv University, IDC Herzliya, Applied Materials, Intuit, and KLA.
I enjoy solving and communicating complex problems and ideas. I develop and deliver Python programming workshops focused on numerical, scientific, and statistical applications in Israel, California, and anywhere else I'm needed - and now also on Zoom.
For more details and offerings click here.