Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
Fundamentals of Reinforcement Learning
Reinforcement Learning is a subfield of Machine Learning, but is also a general purpose formalism for automated decision-making and AI. This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts with the world. Understanding the importance and challenges of learning agents that make decisions is of vital importance today, with more and more companies interested in interactive agents and intelligent decision-making. This course introduces you to the fundamentals of Reinforcement Learning.
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Course by
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Self Paced
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15 ساعات
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الإنجليزية
Machine Learning for Investment Professionals
This course is uniquely tailored to the needs of investment professionals or those with investment industry knowledge who want to develop a basic, practical understanding of machine learning techniques and how they are used in the investment process. Incorporating real-life case studies, this course covers both the technical and the “soft skills” necessary for investment professionals to stay relevant.
In this course, you will learn how to:
-\tDistinguish between supervised and unsupervised machine learning and deep learning
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
Decision Making and Reinforcement Learning
This course is an introduction to sequential decision making and reinforcement learning. We start with a discussion of utility theory to learn how preferences can be represented and modeled for decision making. We first model simple decision problems as multi-armed bandit problems in and discuss several approaches to evaluate feedback. We will then model decision problems as finite Markov decision processes (MDPs), and discuss their solutions via dynamic programming algorithms.
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Course by
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Self Paced
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47 ساعات
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الإنجليزية
How Entrepreneurs in Emerging Markets can master the Blockchain Technology
This course is for entrepreneurs needing to understand the blockchain and distributed ledger technologies that are fundamentally changing how financial and personal data is handled. The course will discuss blockchain as a distributed ledger and introduce distributed consensus as a mechanism to maintain the integrity of the blockchain. The other revolutionary technologies that are changing the world are artificial intelligence and machine learning. You will learn about the three major types of AI algorithms: supervised and unsupervised machine learning, as well as reinforcement learning.
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Course by
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Self Paced
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10 ساعات
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الإنجليزية
Unsupervised Learning, Recommenders, Reinforcement Learning
In the third course of the Machine Learning Specialization, you will: • Use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection. • Build recommender systems with a collaborative filtering approach and a content-based deep learning method. • Build a deep reinforcement learning model. The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online.
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Course by
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Self Paced
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28 ساعات
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الإنجليزية
ML Algorithms
ML Algorithms is the fourth Course in the AWS Certified Machine Learning Specialty specialization. This Course enables learners to deep dive Machine Learning Algorithms. This course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 2:00-2:30 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners.
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Course by
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Self Paced
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5 ساعات
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الإنجليزية
Overview of Advanced Methods of Reinforcement Learning in Finance
In the last course of our specialization, Overview of Advanced Methods of Reinforcement Learning in Finance, we will take a deeper look into topics discussed in our third course, Reinforcement Learning in Finance. In particular, we will talk about links between Reinforcement Learning, option pricing and physics, implications of Inverse Reinforcement Learning for modeling market impact and price dynamics, and perception-action cycles in Reinforcement Learning.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Fundamentals of Machine Learning in Finance
The course aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) understanding where the problem one faces lands on a general landscape of available ML methods, (2) understanding which particular ML approach(es) would be most appropriate for resolving the problem, and (3) ability to successfully implement a solution, and assess its performance.
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Course by
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Self Paced
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18 ساعات
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الإنجليزية
Reinforcement Learning for Trading Strategies
In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Guided Tour of Machine Learning in Finance
This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures.
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Course by
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Self Paced
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24 ساعات
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الإنجليزية
Reinforcement Learning in Finance
This course aims at introducing the fundamental concepts of Reinforcement Learning (RL), and develop use cases for applications of RL for option valuation, trading, and asset management.
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
Deep Learning and Reinforcement Learning
This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised Learning, and is frequently used to power most of the AI applications that we use on a daily basis. First you will learn about the theory behind Neural Networks, which are the basis of Deep Learning, as well as several modern architectures of Deep Learning.
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Course by
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32 ساعات
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الإنجليزية
A Complete Reinforcement Learning System (Capstone)
In this final course, you will put together your knowledge from Courses 1, 2 and 3 to implement a complete RL solution to a problem. This capstone will let you see how each component---problem formulation, algorithm selection, parameter selection and representation design---fits together into a complete solution, and how to make appropriate choices when deploying RL in the real world. This project will require you to implement both the environment to stimulate your problem, and a control agent with Neural Network function approximation.
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Course by
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Self Paced
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16 ساعات
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الإنجليزية
Machine Learning for Trading
This 3-course Specialization from Google Cloud and New York Institute of Finance (NYIF) is for finance professionals, including but not limited to hedge fund traders, analysts, day traders, those involved in investment management or portfolio management, and anyone interested in gaining greater knowledge of how to construct effective trading strategies using Machine Learning (ML) and Python. Alternatively, this program can be for Machine Learning professionals who seek to apply their craft to quantitative trading strategies.
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Course by
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Self Paced
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الإنجليزية
Machine Learning and Reinforcement Learning in Finance
The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on core paradigms and algorithms of machine learning (ML), with a particular focus on applications of ML to various practical problems in Finance. The specialization aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) mapping the problem on a general landscape of available ML methods, (2) choosing particular ML approach(es) that would be most appropriate for resolving the problem, and (3
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Course by
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Self Paced
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الإنجليزية
IBM Machine Learning
Prepare for a career in the field of machine learning. In this program, you’ll learn in-demand skills like AI and Machine Learning to get job-ready in less than 3 months. Machine Learning is the use and development of computer systems that are able to learn and adapt by using algorithms and statistical models to analyze and draw inferences from patterns in data. Machine Learning is a branch of Artificial Intelligence (AI) where computers are taught to imitate human intelligence in that they solve complex tasks.
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Course by
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الإنجليزية
Reinforcement Learning
The Reinforcement Learning Specialization consists of 4 courses exploring the power of adaptive learning systems and artificial intelligence (AI). Harnessing the full potential of artificial intelligence requires adaptive learning systems.
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Course by
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Self Paced
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الإنجليزية