Data Science with Python

Interested in the growing field of data science? Want to learn how to automate data gathering using Python? Ever wonder how to access online APIs? Check out the course details below or sign up now! Presented in collaboration with NTUC U Associates.
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Get hands-on with Python, the powerful and flexible programming language used in many Data Science applications. This introductory course, for business & financial analysts with no prior coding background, will show how you can use Python in your everyday work.

Get started with programming concepts in Python such as loops, conditionals, and functions—critical steps your way to powering your data analysis at a higher level.

Dive into Python using industry-standard tools such as Jupyter notebooks, numpy, and pandas libraries to solve real-world financial and marketing scenarios.

Develop coding capabilities to crack files, secure documents, crawl and sort data, as well as integrate APIs.

Programme Details

 

Dates & Structure

  • 2 days: October 29 & 30 (Monday & Tuesday)

Venue

  • 1 Fusionopolis Way (Map)

Price

  • NTUC Members: $600 (including GST)
  • Public: $800 (including GST)

Note for NTUC members

  • NTUC members enjoy a special rate for this course: Please select the variant with the discounted price before check-out. Please bring your member card/NRIC to the first lesson for on-site membership verification.
  • UTAP funding available: On top of the discount, NTUC members also enjoy 50% unfunded course fee support (capped at $250 per year), claimable from UTAP. Find out more here.

 

Curriculum Details

Each module is designed for a brief introduction and a guided walk-through on programming concepts and abstractions by the instructor, followed by exercises and hands-on to reinforce learning.

Part I: Programming in Python

Introduction to Python

  • Variables, Functions, and Data Types
  • Lists: Indexing and Slicing
  •  Loops
  • Conditionals

Introduction to Dataframes

  • Importing Data
  • Reading and Filtering
  • Inserting, Deleting and Reordering

Part II: Real World Applications

Visualisations in Python

  • Basic dataframe plots with matplotlib
  • More advanced plots with plot.ly

Introduction to APIs

  • Intro to JSON and Python Dictionaries
  • Accessing data from the web via Python
  • Singapore’s Public Data (data.gov.sg)
  • Stock Market Data
  • Automating data collection and cleanup
  • Converting JSON data to a Dataframe

 

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If you have any questions, concerns, or are looking for suggestions, feel free to contact us at [email protected]!