Introduction to Python & Introduction to Data Science Bundle
Introduction to Python for Business and Finance
Tuesday, October 29th, 2019
9 AM - 5 PM
Python is a high-level, object-oriented programming language that is used in a variety of projects ranging from data science and machine learning to backend web development. In fact, it is one of the most in-demand programming languages today.
Learning Python is a great entry point into the technical world as the syntax is much easier to learn compared to other programming languages. Because of its syntax simplicity, Python is a common first programming language for business and finance individuals.
But, do not be misinformed though! Just because Python has easier syntax does not make it any less powerful compared to other languages. Many of the world’s tech majors use Python as part of their technical ecosystems.
This one-day, hands-on introductory course teaches students foundational Python concepts and how to use Python’s popular libraries to complete various technical tasks. Students are presented with Python coding challenges throughout the day to test their understanding of the material. The course culminates with a challenging in-class coding project where students apply concepts taught in the course to create a game.
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Introduction to Data Science & Python for Finance
Wednesday, October 30th, 2019
9 AM - 5 PM
The amount of data available to organizations and individuals is unprecedented. Financial services sectors, including securities & investment services and banking, have the most digital data stored per firm on average. Finance companies that want to maximize use of this available data require professionals who have a keen understanding of data science and know how to use it to solve meaningful business challenges.
This one-day, hands-on course provides a structured teaching environment where attendees learn the Python programming language as a powerful tool to conduct robust data analyses on finance-related data sets. At the end of the workshop, course participants will have applied the Python programming language and essential data analysis techniques to practical programming exercises to gain experience solving challenging finance-related problems.
Specific area in finance where data science skills acquired from this course can be effectively applied include: sentiment analysis, advanced time series analysis, risk management, real-time pricing and economic data analysis, customer segmentation analysis, and machine learning algorithm creation for financial technologies.
No programming experience required.
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