Python Applications for Digital Design and Signal Processing
Python Applications for Digital Design and Signal Processing (Orientation / Kickoff) - 6:00PM - 6:30PM EDT; Thursday, March 26, 2026
Additional videos released weekly in advance of that week’s live session!
Python Applications for Digital Design and Signal Processing (Workshops) - 6:00PM – 7:30PM EDT; Thursdays, April 2, 9, 16, 23
Registration is open through the last live workshop date. Live workshops are recorded for later use.
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https://dsp-coach.com/compliance-ieee
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Registration Fees:
IEEE Member Early Rate (by March 24): $190.00
IEEE Member Rate (after March 24): $285.00
IEEE Non-Member Early Rate (by March 24): $210.00
IEEE Non-Member Rate (after March 24): $315.00
Early registration deadline is: Tuesday, March 24, 2026
Decision to run/cancel course: Tuesday, March 24, 2026
Course Information will be distributed on Tuesday, March 24, 2026 in advance of and in preparation for the first live workshop session. A live orientation session will be held on Thursday, March 26, 2026
Attendees will have access to the recorded session and exercises for two months (until June 23, 2026) after the
last live session ends!
This is a hands-on course combining pre-recorded lectures with live Q&A and workshop sessions in the popular and powerful open-source Python programming language.
Pre-Recorded Videos: The course format has been updated to release pre-recorded video lectures that students can watch on their own schedule, and an unlimited number of times, prior to live Q&A workshop sessions on Zoom with the instructor. The videos will also be available to the students for viewing for up to two months after the conclusion of the course.
Overview: Dan provides simple, straight-forward navigation through the multiple configurations and options, providing a best-practices approach for quickly getting up to speed using Python for modelling and analysis for applications in signal processing and digital design verification. Students will be using the Anaconda distribution, which combines Python with the most popular data science applications, and Jupyter Notebooks for a rich, interactive experience.
The course begins with basic Python data structures and constructs, including key “Pythonic” concepts, followed by an overview and use of popular packages for scientific computing enabling rapid prototyping for system design.
During the course students will create example designs including a sigma delta converter and direct digital synthesizer both in floating point and fixed point. This will include considerations for cycle and bit accurate models useful for digital design verification (FPGA/ASIC), while bringing forward the signal processing tools for frequency and time domain analysis.
Jupyter Notebooks: This course makes extensive use of Jupyter Notebooks which combines running Python code with interactive plots and graphics for a rich user experience. Jupyter Notebooks is an open-source web-based application (that can be run locally) that allows users to create and share visually appealing documents containing code, graphics, visualizations and interactive plots. Students will be able to interact with the notebook contents and use “take-it-with-you” results for future applications in signal processing.
Target Audience: This course is targeted toward users with little to no prior experience in Python, however familiarity with other modern programming languages and an exposure to object-oriented constructs is very helpful. Students should be comfortable with basic signal processing concepts in the frequency and time domain. Familiarity with Matlab or Octave is not required, but the equivalent operations in Python using the NumPy package will be provided for those students that do currently use Matlab and/or Octave for signal processing applications.
Benefits of Attending / Goals of Course: Attendees will gain an overall appreciation of using Python and quickly get up to speed in best practice use of Python.
All set-up information for the installation of all tools will be provided before the start of class.
Date and Time
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- Starts 13 January 2026 02:00 PM UTC
- Ends 26 March 2026 10:30 PM UTC
- Admission fee ?
Speakers
Dan Boschen
Python Applications for Signal Processing and Digital Design
Biography:
Dan Boschen "The DSP Coach" (dsp-coach.com)
Dan Boschen has a MS in Communications and Signal Processing from Northeastern University, with over 25 years of experience in system and hardware design for radio transceivers and modems. He has held various positions at Signal Technologies, MITRE, Airvana and Hittite Microwave designing and developing transceiver hardware from baseband to antenna for wireless communications systems and has taught courses on DSP to international audiences for over 15 years. Dan is a contributor to Signal Processing Stack Exchange https://dsp.stackexchange.com/, and is currently at Microchip (formerly Microsemi and Symmetricom) leading design efforts for advanced frequency and time solutions.
Address:United States
Agenda
Topics / Schedule:
Pre-recorded lectures (3 hours each) will be distributed Friday prior to all Workshop dates. Workshop/ Q&A Sessions are 6pm-7:30pm on the dates listed below:
Kick-off / Orientation: March 24, 2026
Thursday, April 2, 2026
Topic 1: Intro to Jupyter Notebooks, the Spyder IDE and the course design examples. Core Python constructs.
Thursday, April 9, 2026
Topic 2: Core Python constructs; iterators, functions, reading writing data files.
Thursday, April 16, 2026
Topic 3: Signal processing simulation with popular packages including NumPy, SciPy, and Matplotlib.
Thursday, April 23, 2026
Topic 4: Bit/cycle accurate modelling and analysis using the design examples and simulation packages