Vorlesungsverzeichnis 

Vorlesung im Detail

Programming Course: Date Science with Python

Nummer
010562C, WS2526
Dozentinnen und Dozenten
Veranstaltungstyp (SWS)
Kompaktkurs (3)
Ort und Zeit
  • M/CIP Mi 10:00 2h
Modul-Zugehörigkeit (ohne Gewähr)
  • DPL:A:-:-
  • DPL:F:-:1
Sprechstunde zur Veranstaltung
nach Vereinbarung
Anmeldung?
ohne Angabe
Inhalt
The course is elective as a 'Programming Course' for the MD 3 module (Data Science in Practice) ca. 3-4 hours per week (April - July). Data Science with Python Course description This course will help you raise your level from a beginner’s to an advanced one using the programming language Python. You’ll be learning about libraries like NumPy, Pandas and how to visualize your Dataset with Matplotlib and Seaborn. Not to mention learning about the many important statistical concepts in the Data Science Domain and it’s application using your knowledge about Python. Lastly you’ll learn about Machine learning using SciKit-Learn. Practical sessions will teach you how to apply your knowledge and you will get more and more confident in using it.
Course content:
Introduction to jupyter notebook
Basics of Python
Variables and simple data types
Lists
Dictionaries
Tuples
Set and Booleans
Comparison Operators

Python Statements:
If, elif and else Statements
For Loops
While loops

Methods
Functions
Files and Exceptions
Modules

Built-in modules
OS Modules
Python Code Timing and Profiling


Object Oriented Programming
Python for Data Science
Numpy
Pandas

Data Visualization:
Matplotlib
Seaboarn

Python Statistical analysis:
Characterising
Intrdouction to summary statistics
Central Tendency
Dispersion
Joint Variability
Empirical CDF
Scikit-Learn:
Dataset Preparation
Machine Learning Algorithm
Supervised Learning
Unsupervised Learning
Algorithm Evaluations
Bemerkungen
Link zu den Modulbeschreibungen im Service

The course is elective as a 'Programming Course' for the MD 3 (Data Science in Practice),ca. 3-4 hours per week (October-February).
Empfohlene Literatur
  • will be announced

Übung zur Veranstaltung

Nummer der Übung
010562C
Dozentinnen und Dozenten
Übungsgruppen
  • M/CIP Mi 12:00 2h

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