Python Training

Python for Finance

This is a course for financial analysts, traders, risk analysts, fund managers, researchers, data scientists, statisticians, and software developers interested in learning to use Python for analysing and visualising financial market data.

Prerequisites

Some familiarity with programming concepts (in any language) is assumed.

Expected Outcomes

By the end of the course, you will have all the knowledge you need to start using Python competently for processing, analysing, modelling, and visualising various kinds of financial data, with a focus on time series. You will have had experience with using Python for various scripting, data-manipulation and plotting tasks with data in a variety of formats, including CSV, Excel spreadsheets, SQL databases, JSON, and API endpoints, as well as log files and unstructured text. You will have applied powerful tools for optimisation, regression, classification, and clustering, in useful practical settings on small and large data sets. You will understand the elegance and power of the Python language and its powerful ecosystem of packages for data analysis, and you will be well-placed to continue learning more as you use it day-to-day.

Course Syllabus

Day 1: Python Basics

Day 1 covers how to use Python for basic scripting and automation tasks, including tips and tricks for making this easy.

  • Why use Python for finance? What’s possible? Python versus Java, C#, R, Matlab …
  • Setting up your Python development environment (IDE, IPython notebook)
  • Python syntax and concepts: an introduction through examples, including
  • Functions
  • Essential data structures: strings, tuples, lists, dictionaries and sets, and their applications
  • Input and output of text data (including CSV files)
  • String methods
  • Raising and handling exceptions
  • Tour of the amazing standard library, including
  • Handling dates and times
  • Fetching data from the web
  • Serialization
  • Compressing and uncompressing data
  • Day 2: Essential analytic tools and data formats

    The Pandas package is an amazingly productive tool for working with and analysing data in Python. Day 2 gives a thorough introduction to Pandas and related tools for working with different kinds of data, including spreadsheets, time-series data, and SQL databases.

  • Fast, powerful data analysis with Pandas: Indexing, grouping, merging, reshaping, pivoting, summarising data
  • Intro to NumPy for efficiently handling numerical data
  • Working with missing and noisy data
  • Working with essential financial data formats: CSV, Excel, SQL, JSON, HDF5, XML (as needed)
  • Statistical graphics and visualisation of data using Pandas, Matplotlib, and Seaborn
  • Day 3: Analysing and presenting financial data

    Day 3 focuses on techniques for modelling and visualising financial time-series data and creating reports. It also introduces some of the most fundamental and powerful Machine Learning techniques for analysing many kinds of real-world data in Python: classification, regression, and clustering.

  • Regression and time-series analysis with Pandas, SciPy and Statsmodels
  • Introduction to machine learning with scikit-learn for time-series data:
  • Classification with scikit-learn, with application to diagnosis and prediction
  • Linear and nonlinear regression with statsmodels and scikit-learn, with application to quality assessment and forecasting
  • Clustering of data using scikit-learn, with application to outlier detection
  • We also encourage you to bring your own data sets to the course where relevant.

    Custom topics

    We are happy to customise the above syllabus upon request to include other topics.

    Supplemental materials

    We will supply you with printed course notes and a USB stick containing a complete Python environment based on VirtualBox. This saves time in the course and allows us to focus on using Python rather than installing it. The USB stick also contains kitchen-sink Python installers for multiple platforms, solutions to the programming exercises, several written tutorials, and reference documentation on Python and the third-party packages covered in the course.

    Other information

    Personal help:
    Your trainer(s) will be available after the course each day for you to ask any one-on-one questions you like — whether about the course material and exercises or about specific problems you face in your work and how to use Python to solve them.
    Food and drink:
    We provide lunch, morning and afternoon tea, and drinks in our open courses.
    Timing:
    The course will run from 9:00 to roughly 17:00 each day, with a breaks of 45 minutes for lunch and 15 minutes each for morning and afternoon tea.

    Upcoming Courses

    24/07/2017 at Sydney

    We also offer custom courses on-site for teams within organisations. These are particularly appropriate if your team uses particular tools or data sources in its workflow. Please contact us to discuss your requirements.

    Upcoming Public Courses

    Canberra

    Python for Scientists & Engineers:
    08 May – 11 May 2017

    View Details Book Now

    Canberra

    Python for Geospatial Analysis:
    08 May – 12 May 2017

    View Details Book Now

    Introduction To Qgis

    Python for Geospatial Analysis:
    15 May – 16 May 2017

    View Details Book Now

    Melbourne

    Python for Scientists & Engineers:
    10 Jul – 13 Jul 2017

    View Details Book Now

    Melbourne

    Python for Geospatial Analysis:
    10 Jul – 14 Jul 2017

    View Details Book Now

    Sydney

    Python for Finance:
    24 Jul – 27 Jul 2017

    View Details Book Now

    Sydney

    Python for Scientists & Engineers:
    14 Aug – 18 Aug 2017

    View Details Book Now

    Location

    Testimonials

    “One of the best programming courses I have attended - thanks!”

    - Giant Billen, IAG Insurance

    “Excellent training course, excellently presented. Perhaps the best that I have had in the area of IT / programming.”

    - George Grozev, CSIRO (Clayton)

    “Both Ed and Henry presented well…. The course structure was adjusted to suit the participants quickly and easily.”

    - Jenet Austin, CSIRO (Black Mountain Laboratory)

    “Course content was well presented and easily digested. Practical exercises were an essential part of the course – a good ratio of lecture/play was achieved. Well done Ed and Henry!”

    - Steve Zegelin, CSIRO (Black Mountain Laboratory)

    “Very comprehensive intro to every aspect of python. Highly qualified trainer. Beyond my expectation on every aspect. ”

    - Baichuan Sun, CSIRO (Clayton)

    “I loved it. Ed was inspiring.”

    - Onoriode Coast, CSIRO (Narrabri, NSW)

    “One of the best training courses I've been on.”

    - David Scurrah, Bureau of Meteorology (Melbourne)

    “Instructor was superb - very impressive. I really enjoyed the course - thanks!”

    - Steven Edgar, CSIRO (Hobart)

    “Simply awesome!!”

    - James Park, Cisco (St Leonards)

    “It was a pleasure ... Shared feedback from all involved was that it’s been one of the most beneficial and well delivered training courses we’ve been a part of.”

    - Dylan Matthews, Simply Energy / GDF Suez (Melbourne)

    “Very impressed with the course, delivery. And depth of knowledge of Ed and Henry. Far exceeded my expectations and has greatly improved my core skills as well as inspired so many new ideas for my current work / projects. Thank you!”

    - Kelsey Druken, National Computational Infrastructure (Canberra)

    “The course was delivered by trainers who were extremely knowledgeable in their field. It was really good to learn from the best!”

    - Marius Roman, Transurban (Melbourne)

    “Really impressed by Python's capability and excited to use as alternative to MatLab, as is free and better supported.”

    - Carsten Hofmann, OMC International (Melbourne)

    “Was the most fulfilling and rewarding class I have taken since "general relativity" at uni. Was extremely well run. Excellent all round!”

    - Dr Millicent Maier, Australian Astronomical Observatory (Sydney)

    “This course has shown me how I could have done the work I was doing just last week 10x more efficiently in Python.”

    - Maruf Rahman, Geoscience Australia (Canberra)

    “The VM setup and USB is great. Ed is an excellent instructor - he presents well and welcomes any questions. He is clearly a super smart guy who has a great grasp on what he is teaching - able to just prototype on the fly and the course overall really opened my eyes to python. ”

    - Jack Hendy, Optiver (Sydney)

    “Great course. Enjoyed it and will follow up with some practical implementation of some of the work.”

    - Adam Grace, Optus (Sydney)