BENEFIT FROM A 20% EARLY BIRD DISCOUNT AVAILABLE UNTIL 19 MARCH 2019 This one-day training
BENEFIT FROM A 20% EARLY BIRD DISCOUNT AVAILABLE UNTIL 19 MARCH 2019
This one-day training course, delivered by CFA Switzerland in partnership with Cognitir, provides a structured teaching environment where you can learn classic data science methods which are used as the bases for many financial technologies. At the end of the workshop, course participants will have applied the Python programming language and essential data science techniques to solve complex financial problems.
Key learning outcomes
- An overview of data science methods relevant to finance and fintech.
- Hands-on Python programming experience.
- Understanding of effective data visualization techniques using Python.
What this course offers?
- Course notes, certificate of completion and post-course email support for 3 months.
- An engaging and practical training approach with a qualified instructor with relevant technical, business and educational experience.
Who is this course for?
This course is designed for professionals who want to gain a hands-on introduction to essential data science methods that are used in finance and fintech.
- Introduction to Data Science for Finance & Fintech
- What is data science, why is it relevant to finance & fintech
- Applications of data science to finance & fintech industries
- The Data Science Process
- How does the data science process typically look like within an organisation?
- Overview of the main steps
- Pitfalls & recommendations
- Overview of the Most Common Data Science Methods
- Supervised vs. unsupervised learning
- Classification in Python for Finance & Fintech
- When to use classification tasks
- Overview and implementation of decision tree classification in Python toobtain better customer insights
- Evaluation of classification tasks using accuracy, confusion matrices,expected value, etc.
- Visualisation classification tasks using profit curves, ROC curves, AUC, etc.
- Selecting informative attributes via information gain and entropy analyses
- Clustering in Python for Finance & Fintech
- When to use clustering task
- Improving k-means and using similarity for predictive modeling
- Overview and implementation of k-means clustering in Python to understandstock data and optimize portfolios
- Big Data for Finance
- What is big data and why is big data relevant to finance & fintech
- How does big data relate to the concepts taught in this course
- Overview of most common big data technologies
- Wrap-Up and Summary
- Beginner’s knowledge of Python is required as contained in units 1-8 of this free online Python course.
- Please bring your own laptop.