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+## Updates
+- https://pythonnumericalmethods.studentorg.berkeley.edu/notebooks/Index.html
+- Numerical Methods for Engineers Steven C Chapra
+
+---
+## Topics
+and questions
+
+- Decide on textbook 
+
+---
+## Discussion 
+
+
+---
+## Actions
+- Send Ciprian PDF of Numerical methods PDF
+
+
+- Ciprian to look at textbook in more detail and make a decision by next time.
+- Christian to send PDF of the second book by Steven Chapra
+
+Module 4: Data Analysis and Processing  
+
+- 4.1. Introduction to Data Analysis (describe the Panda Toolbox)  -> One Lecture
+- 4.2. We should focus on effective ways of looking at data  (philosophy of making that make sense) -> One Lecture
+- 4.2. I/O file handling (different types of data files: ASCII, CSV, TXT, JPEG,...) -> Here they will learn how to read/handle: datasets including images. -> One Lecture
+- 4.3. Statistical Analysis (mean/averaging, standard deviation, variance...) -> **_Reminder: Ciprian to send application from Spectroscopy and CFD -> One Lecture_**
+- 4.4. Data Cleaning (linear regression, least square fitting, extrapolation, moving average) -> One Lecture
+- 4.5. Data Filtering & Signal Processing (filters: Gaussian Filter, Sobel edge detection, Kalman, Butterworth, FFT) -> We need to give a lecture of what is/how it works Digital filter design (lowpass, highpass, bandpass, filter response curves, how does one select a given filter). One lecture all theory so that in the second lecture they learn how to select different filters. -> Two lectures
+- 4.6 Image processing: apply some of the filtering to make images sharper/crispier, teach them how to make videos/gifs out of images. -> One Lecture. Possible application: **_from CFD density data obtain Synthetic Schlieren images (Ciprian will send you this!)_**
+ 
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