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SUMMARY:OT-ST-WS-04 Getting started with Python
DTSTART:20261102T080000Z
DTEND:20261104T160000Z
DTSTAMP:20260819T232400Z
UID:indico-event-25@events.bremen-research.de
CONTACT:data-train@vw.uni-bremen.de\;+49 (421) 218 60043
DESCRIPTION:Speakers: Data Train UBRA (U Bremen Research Alliance)\n\nBack
 ground\nData analysis is essential in today’s digital age\, where enormo
 us amounts of data are generated across every industry. Python\, with its 
 simple syntax and robust data libraries\, empowers you to transform raw da
 ta into clear\, actionable insights that drive informed decision-making.\n
 Learning contents\nThis course is designed to introduce data analytics usi
 ng Python through a series of practical modules. It begins with the basics
 \, covering Python syntax\, variables\, data types\, and fundamental opera
 tions\, as well as writing simple scripts to automate your workflow. You'l
 l work with Python's core data structures\, such as lists\, dictionaries\,
  and sets\, which form the backbone of efficient data management.As the co
 urse progresses\, you'll learn to import and manipulate data using popular
  libraries like Pandas and NumPy. You'll gain hands-on experience cleaning
 \, transforming\, and wrangling datasets\, and you'll explore methods for 
 reading from and writing to common file formats like CSV and Excel. Additi
 onally\, you'll enhance your programming skills by developing custom funct
 ions for routine analytic tasks.In the later stages\, the course covers ba
 sic statistical techniques—including regression analysis and principal c
 omponent analysis (PCA)—to help you extract meaningful insights from you
 r data. Finally\, you'll build your skills.\nLearning objectives\nPython F
 undamentals: Understand Python syntax\, variables\, data types\, and contr
 ol structures to build a strong coding foundation.\n\nCore Data Structures
 : Gain proficiency with lists\, dictionaries\, sets\, and other essential 
 data structures to effectively store and manipulate data.\nScript Automati
 on: Learn to write and run scripts that automate repetitive tasks and stre
 amline your workflow.\nData Handling with Libraries: Develop hands-on expe
 rience with key Python libraries like Pandas and NumPy to import\, clean\,
  transform\, and export data from common file formats such as CSV and Exce
 l.\nCustom Function Development: Build the skills to write custom function
 s that simplify and automate common analytical tasks.\nStatistical Analysi
 s: Apply basic statistical techniques\, including regression analysis and 
 principal component analysis (PCA)\, to extract meaningful insights from d
 ata.\nData Visualization: Master the use of visualization libraries like S
 eaborn to create clear and effective data visualizations that communicate 
 results.\n\nPrior knowledge\nBasic Computer Skills: Participants should be
  comfortable using a computer for file management and simple tasks.\nNo Pr
 ogramming Experience Required: This beginner course is designed with the a
 ssumption that learners have little or no prior experience in programming 
 or Python.\nBasic Data Handling Familiarity (Optional): While not essentia
 l\, familiarity with basic data organization—such as using spreadsheets 
 (e.g.\, CSV or Excel files)—can be beneficial.\nEagerness to Learn: A wi
 llingness to engage with hands-on exercises and explore new tools is key t
 o success in this course.\nTechnical requirements\n\nOwn laptop\n\nConnect
 ion to Wifi via eduroam or equivalent access (see: https://www.uni-bremen.
 de/en/zfn/wifi/overview-wifi)\n\nAccess to Python\n\nPlease make sure\, yo
 u have a functional Python environment running before the workshop\nPartic
 ipants with access to the Uni Bremen ZfN Services can use Python via Jupyt
 erHub (https://jupyter.uni-bremen.de/).\n\n\nIf you do not have any progra
 mming environment (e.g. Python\, R\, Rstudio\, etc.) installed on your com
 puter\, you can use web-based options: For example\, participants with acc
 ess to the Uni Bremen ZfN Services can use the Uni Bremen JupyterHub. Alte
 rnatively\, participants can use the NFDI JupyterHub.\n\nThe Lecturers\n\n
 \n\n\nDr. Sonja Hänzelmann + Team\nSonja Hänzelmann is Head of Data Scie
 nce at Alfred Wegener\, Helmholtz Center for Polar und Marine Research\, B
 remerhaven.\n\n \n\n\n\n\n \n\n\n\n \nFind out more about the Data Trai
 n lecturers on our website.\n \nThis event is organized by\n\n\nhttps://e
 vents.bremen-research.de/event/25/
LOCATION:Room 2.2070/2.2090 (2. floor) (Unicom 2 (Haus Oxford))
URL:https://events.bremen-research.de/event/25/
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