Yoav Ram

Python Training for Engineers, Data Scientists, and Everyone

About

‐ Faculty at School of Computer Science, IDC Herzliya
‐ Postdoctoral fellow at Stanford University
‐ PhD in Mathematical & Computational Biology from Tel Aviv University
‐ Excellence in Teaching Award from the Faculty of Engineering, Tel Aviv University

‐ Programming with Python since 2002
‐ Teaching Python since 2011
‐ Specializing in Data Science & Scientific Computing with Python:
  Jupyter, NumPy, SciPy, Matplotlib, Pandas, Scikit-learn, Keras & TensorFlow
‐ Based in Israel and California, available Worldwide

I develop and give Python programming courses with focus on numerical, scientific, and statistical applications. To enhance participant learning, all course material is fully interactive, using Jupyter notebooks, and all lectures include hands-on exercises.

Browse the offered courses below or contact me for customized courses.

Testimonials

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Courses

Python for Engineers

Python Programming for MATLAB® Users

The course is intended for engineers with MATLAB® experience that are interested in applying their knowledge and skills using the Python programming language.

The course combines practical programming skills in the Python programming language with a comprehensive overview of major numerical, mathematical, and statistical libraries. The course is taught entirely using interactive notebooks and includes hands-on exercises.

  • Four-five days, 32-40 hours of interactive lectures in a computer lab
  • Built-in exercises
  • Python 3.7
  • All course material in interactive Jupyter notebooks
  • Topics:
    • Basic Python
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    • Idiomatic Python
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    • Object Oriented Programming
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    • I/O
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    • N-dimensional arrays
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    • Plotting & Visualizations
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    • Linear algebra
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    • Calculus
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    • Digital signal processing
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    • Image analysis
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    • Statistics
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    • Stochastic processes
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    • Curve fitting
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    • Optimization
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    • Machine learning
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    • Deep learning
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    • Symbolic mathematics
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    • High performance computing
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    • Testing and debugging
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    • User interfaces
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    • RESTful web services
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    • Monitoring and event scheduling
  • Python libraries:

Course repo Introduction Preview

Introduction to Python

One Day Workshop on Data Science with Python for Developers and Engineers

This one day workshop is intended for software developers and engineers interested in a quick introduction to the Python programming language and its use for data science.

The one day workshop combines an introduction to the basics of the Python programming language with a preview of the common tools used for data analysis and visualization. The workshop is taught entirely using interactive notebooks and includes hands-on exercises.

Preview

Machine Learning and Deep Learning with Python

One Day Workshop on Data Analysis, Machine Learning and Deep Learning with Python

The workshop is intended for developers and engineers with Python experience interested in machine learning and deep learning with Python.

The one day workshop provides an introduction to common tools used for data analysis and visualization in Python and to libraries used for machine learning (scikit-learn) and deep learning with neural networks (TensorFlow). The course is taught entirely using interactive notebooks and includes hands-on exercises.

  • 8 hours of interactive hands-on sessions
  • Built-in exercises
  • Python 3.7
  • All course material in interactive Jupyter notebooks
  • Topics:
    • Data processing and analysis
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    • Plotting & Visualizations
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    • Machine learning
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    • Deep learning
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    • Convolutional neural networks
  • Python libraries:

Preview

Python for Biologists

Python Programming for Life Science Researchers

The course is intended for researchers in biology and medicine interested in extending their knowledge and skills in programming and computational biology.
The course was developed and taught at the Faculty of Life Sciences in Tel-Aviv University during Spring semester 2015.

The course combines practical programming skills in the Python programming language with computational modeling and analysis of biological data. For example, students do sequence data analysis, mathematical modeling of population dynamics, and statistical analysis and visualization of experimental and observational results.

  • 20 hours of interactive lectures in computer lab
    • Seven homework exercises
  • Mini research projects and a poster session
  • Two hour exam in computer lab
  • Python 3.4
  • All course material in IPython notebooks
  • Python libraries:

Course site Course repo

Numerical Computing with Julia

Julia Programming for Engineers and Data Scientists

The course is intended for engineers data scientists interested in applying their knowledge and skills using the Julia programming language.

The course combines practical programming skills in the Julia programming language with an overview of major numerical, mathematical, and statistical libraries. The course is taught entirely using interactive notebooks and includes hands-on exercises.

  • 1-2 days, 8-16 hours of interactive lectures in a computer lab
  • Built-in exercises
  • All course material in interactive Jupyter notebooks
  • Sample topics:
    • Intro Julia
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    • Multiple dispatch
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    • I/O
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    • Plotting & Visualizations
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    • Linear algebra
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    • Calculus
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    • DSP & Image analysis
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    • Statistics
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    • Stochastic processes
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    • Curve fitting
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    • Optimization
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    • Machine learning
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    • Deep learning
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    • High performance computing
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    • Testing and debugging
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