COURSE DETAILS
This introductory course, geared towards financial professionals will discuss key concepts needed to write and understand Python. Rather than overwhelming you with all the syntactical details, we will focus on the key elements and packages giving you just enough orientation to start your Data Science journey in Python.
Using QuAcademy, our remote-learning platform and Jupyter notebooks, we will discuss the key elements of Python and discuss how to write applications working with datasets.
CFA Institute is offering this course, powered by QuantUniversity. This course is eligible for Professional Learning Credits.CFA Institute members are eligible for an additional $100 off! Use coupon "CFAQU100" for a $100 discount on non-member prices.
Note: All courses come with 90-day access to course materials and recordings Qu.Academy from the activation/class-start date. You can extend access to Qu.Academy.
Delivery
LIVE-Online
Number of Modules
4 modules
Each module
3.5 Hours/module
June 21, June 23, June 28, June 30, 7.30AM EDT
June 21, June 23, June 28, June 30, 1.30PM CET
Oct 5, Oct 12, Oct 19, Oct 26, 1.00PM EST
Oct 5, Oct 12, Oct 19, Oct 26, 6.00PM CET
Register
MODULES 1: THE BASICS
Introduction to Python
- The Data Science Revolution: Why you need to learn Data Science now!
- Introduction to Python through examples
- The Python Ecosystem: Popular Data Science and analysis packages
- Lab: Working with Jupyter notebooks
- Exploring data in Python: Time series and Cross-sectional datasets
- Case study 1: Implementing an analytics library in Python for risk and performance calculations
MODULES 2: DATA SCIENCE METHODS
Analyzing data and Visualization
- Understanding relationships in Data
- Descriptive, Prescriptive and Predictive analytics
- Lab: Implementing quantitative methods and metrics
- Exploring and Visualizing Data using pandas, matplotlib, seaborn & plotly
- Case study 2: Visualizing stock portfolios
MODULES 3: MACHINE LEARNING TECHNIQUES
The power of machine learning
- Supervised, Unsupervised and Reinforcement Learning
- Lab: Clustering Stock Data
- Time series analysis and forecasting
- Case study 3: Predicting stock returns using machine learning techniques
MODULES 4: CASE STUDIES & PRACTICAL APPLICATIONS IN FINANCE
Data Science in Action
- Integrating, fundamental, quantitative and Data Science techniques within your enterprise - A roadmap
- Case study 4: Extracting sentiments from Edgar filings using NLP techniques
- Case study 5: Portfolio management with Python
- Recap, next steps and frontier topics: Reinforcement learning, Quantum Computing, AI, GPU-accelerated and Cloud computing
SAMPLE FREE LECTURE
Check out Sri's recent lecture at the CFA Institute and experience QuAcademy to get a feel for the course!
See Lecture
PAST ATTENDEES
Past Attendees of QuantUniversity workshops include Assette, Baruch College, Bentley College, Bloomberg, BNY Mellon, Boston University, Datacamp, Fidelity, Ford, Goldman Sachs, IBM, J.P. Morgan Chase, MathWorks, Matrix IFS, MIT Lincoln Labs, Morgan Stanley, Nataxis Global, Northeastern University, NYU, Pan Agora, Philips Health, Stevens Institute, T.D. Securities and many more..
