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Unlock Portfolio Management Value With Machine Learning

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oaxino

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Unlock Portfolio Management Value With Machine Learning

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Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 757.75 MB | Duration: 0h 57m​

Leverage Machine Learning to Optimize Portfolio Management, Drive Strategic Decisions, and Maximize Business Impact


What you'll learn
Understand the key principles of modern portfolio management
Leverage machine learning to enhance decision-making in portfolio management
Align portfolios with business goals for optimal performance
Implement actionable strategies to adapt to changing environments
Requirements
There are no specific tools or advanced skills required to take this course
However, a basic understanding of portfolio management and machine learning concepts, like supervised and unsupervised learning, will help you get the most out of the content
Description
Unlock the full value of modern portfolio management by integrating the power of Machine Learning into your strategic approach. This course is designed to help you drive significant improvements in portfolio performance through data-driven insights, efficient resource allocation, risk management, and stakeholder engagement. You will learn how to assess and align projects in your portfolio with key business objectives, ensuring that resources are focused on high-impact initiatives while addressing misalignments through strategic adjustments or termination.Through practical applications, you'll discover how Machine Learning can enhance your ability to forecast trends, identify project risks, and adapt your portfolio to changing market conditions, particularly in fast-evolving sectors like eMobility and AI. By leveraging these advanced techniques, you can make informed decisions that not only boost project success but also future-proof your portfolio against unforeseen challenges.This course covers essential elements such as strategic alignment, resource optimization, risk mitigation, and the importance of engaging stakeholders effectively. You'll explore how to build a flexible, adaptive portfolio that can quickly pivot in response to new opportunities, while maintaining a focus on long-term objectives.Whether you're a portfolio manager, business leader, or decision-maker, this course equips you with the knowledge and tools to harness Machine Learning and transform your portfolio management practices, delivering long-lasting value and competitive advantage in today's complex business environment.
Overview
Section 1: Welcome & Introduction to Portfolio Management
Lecture 1 Welcome and Introduction
Lecture 2 Who This Course is For & Prerequisites
Lecture 3 Course Structure Overview
Lecture 4 What You'll Learn
Lecture 5 Final Note on Participation and Reviews
Lecture 6 Setting the Stage
Lecture 7 The Role of Portfolio Management
Lecture 8 What is a Portfolio?
Lecture 9 Machine Learning and Portfolio Management
Lecture 10 Conclusion of Introduction
Section 2: Key Elements of Portfolio Management
Lecture 11 Key Elements of Portfolio Management
Section 3: Implementation of Portfolio Management
Lecture 12 Introduction to Portfolio Management Implementation
Lecture 13 Identifying Key Business Drivers
Lecture 14 Select a Pilot Portfolio
Lecture 15 Implement Performance Monitoring Tools
Lecture 16 Performance Monitoring: Performance Metrics and Monitoring
Lecture 17 Performance Monitoring: Resource Optimization
Lecture 18 Performance Monitoring: Risk Management
Lecture 19 Performance Monitoring: Flexibility and Adaptability
Lecture 20 Performance Monitoring: Stakeholder Engagement
This course equips portfolio managers and business leaders with a deep understanding of portfolio management fundamentals.,It also introduces key machine learning techniques that can enhance decision-making.,While the course doesn't dive into complex ML algorithms, it provides actionable steps that you can discuss and implement with an ML expert, enabling you to leverage these advanced tools to optimize your portfolio.
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oaxino salamat sa pag contribute. Next time always upload your files sa
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