Python and Machine-Learning for Asset Management with Alternative Data Sets
Investment Management with Python and Machine Learning,
Over-utilization of market and accounting data over the last few decades has led to portfolio crowding, mediocre performance and systemic risks, incentivizing financial institutions which are looking for an edge to quickly adopt alternative data as a substitute to traditional data. This course introduces the core concepts around alternative data, the most recent research in this area, as well as practical portfolio examples and actual applications. The approach of this course is somewhat unique because while the theory covered is still a main component, practical lab sessions and examples of working with alternative datasets are also key. This course is fo you if you are aiming at carreers prospects as a data scientist in financial markets, are looking to enhance your analytics skillsets to the financial markets, or if you are interested in cutting-edge technology and research as they apply to big data. The required background is: Python programming, Investment theory , and Statistics. This course will enable you to learn new data and research techniques applied to the financial markets while strengthening data science and python skills.
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| Rating | 4.7★ based on 7 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 4 weeks of study, 2 hours per week |
| Starts | Jul 3 (42 weeks ago) |
| Cost | $49 |
| From | EDHEC Business School via Coursera |
| Instructors | Gideon OZIK, Sean McOwen |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science Business |
| Tags | Data Science Data Analysis Business Finance |
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What people are saying
course 4 clearly paid
I had been a bit disappointed by Course 3 of the Specialization, but this Course 4 clearly paid back !
bit disappointed by course
including latest research topics.both
Highly relevant and including latest research topics.Both lectures and labs are very efficient in delivering state-of-the-art contents.
lab not adding lots
Lab not adding lots of value.
application sections greatly open
In addition, the research application sections greatly open the applications to advanced studies and increase curiosity for the topic.
right balance between theory
Very well-constructed course, right balance between theory, lab sessions and application.
no technical issues
No technical issues.
way better than
Way better than the third course in the Specialization.
delivering state-of-the-art contents
3-sections structure for
The 3-sections structure for each week is really great, the theory is well explained and the lab sessions are very clear, this allows us to really grasp the concepts and be able to use them in the future.
really interesting readings
Really interesting readings in the application section.
highly relevant
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
Account Coordinator, Financial Markets Group $52k
Wall Street and Financial Markets Reporter $63k
Financial Markets Specialist Manager $83k
Financial Markets Operations $87k
Financial Analyst-Capital Markets $88k
Financial Markets Analyst/Trader $93k
Senior Financial Analyst, Capital Markets $94k
Financial Markets Operations Consultant $95k
Associate Financial Markets Analyst $120k
Financial Analyst Capital Markets $137k
Financial Analyst - Emerging Markets $140k
Principal Financial Analyst, Capital Markets $141k
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| Rating | 4.7★ based on 7 ratings |
|---|---|
| Length | 5 weeks |
| Effort | 4 weeks of study, 2 hours per week |
| Starts | Jul 3 (42 weeks ago) |
| Cost | $49 |
| From | EDHEC Business School via Coursera |
| Instructors | Gideon OZIK, Sean McOwen |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Data Science Business |
| Tags | Data Science Data Analysis Business Finance |
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