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Link: magnet:?xt=urn:btih:6958882ae78a586a4d7b19494c564da6d4a67ecc&dn=Python%20For%20Finance%20-%20Data%20Analytics%20And%20Investment%20Strategies%20--%3E%20[%20DevCourseWeb%20]&tr=udp%3A%2F%2Fopen.stealth.si%3A80%2Fannounce&tr=udp%3A%2F%2Fexodus.desync.com%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker.cyberia.is%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker.opentrackr.org%3A1337%2Fannounce&tr=udp%3A%2F%2Ftracker.torrent.eu.org%3A451%2Fannounce&tr=udp%3A%2F%2Fexplodie.org%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker.birkenwald.de%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker.moeking.me%3A6969%2Fannounce&tr=udp%3A%2F%2Fipv4.tracker.harry.lu%3A80%2Fannounce&tr=udp%3A%2F%2Ftracker.tiny-vps.com%3A6969%2Fannounce
Published 1/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.46 GB | Duration: 6h 51m
Master Python for Finance: Data Analytics, Investment Strategies, and Machine Learning Applications
What you'll learn
Gain proficiency in Python programming for financial data analysis, including data preprocessing, visualization, and advanced statistical techniques.
Understand and apply key investment strategies, portfolio optimization methods, and risk management techniques in real-world scenarios.
Learn to implement machine learning and reinforcement learning models for financial applications, such as algorithmic trading and credit risk assessment.
Master advanced financial concepts like derivatives pricing, Monte Carlo simulations, and time series analysis using Python.
Requirements
A basic understanding of finance concepts is helpful but not mandatory.
No prior programming experience is required; all necessary Python fundamentals are covered.
A computer with internet access to install Python and required libraries.
A willingness to learn and explore finance and Python programming.
Published 1/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.46 GB | Duration: 6h 51m
Master Python for Finance: Data Analytics, Investment Strategies, and Machine Learning Applications
What you'll learn
Gain proficiency in Python programming for financial data analysis, including data preprocessing, visualization, and advanced statistical techniques.
Understand and apply key investment strategies, portfolio optimization methods, and risk management techniques in real-world scenarios.
Learn to implement machine learning and reinforcement learning models for financial applications, such as algorithmic trading and credit risk assessment.
Master advanced financial concepts like derivatives pricing, Monte Carlo simulations, and time series analysis using Python.
Requirements
A basic understanding of finance concepts is helpful but not mandatory.
No prior programming experience is required; all necessary Python fundamentals are covered.
A computer with internet access to install Python and required libraries.
A willingness to learn and explore finance and Python programming.