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ESG Investing: Financial Decisions in Flux

ESG Investing: Financial Decisions in Flux

As ESG investing continues to evolve towards a global standard, certain initiatives such as the UN’s sustainable development goals, and the Paris Agreement on climate change, have already spurred significant changes across the financial markets. As the title of this specialization suggests, financial decisions by investors, as well as capital deployment by companies, organizations, and governments, have been shifting amid increasing attention to environmental, social, and governance-related concerns. By the end of this specialization, students with basic knowledge of traditional financial pr

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Building a Large-Scale, Automated Forecasting System

Building a Large-Scale, Automated Forecasting System

In this course you learn to develop and maintain a large-scale forecasting project using SAS Visual Forecasting tools. Emphasis is initially on selecting appropriate methods for data creation and variable transformations, model generation, and model selection.

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  • 10 ساعات
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Matrix Methods

Matrix Methods

Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Discover the Singular Value Decomposition that plays a fundamental role in dimensionality reduction, Principal Component Analysis, and noise reduction. Optional examples using Python are used to illustrate the concepts and allow the learner to experiment with the algorithms.

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  • 7 ساعات
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Mathematics for Machine Learning

Mathematics for Machine Learning

For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to how it’s used in Computer Science.

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MATLAB Programming for Engineers and Scientists

MATLAB Programming for Engineers and Scientists

This Specialization aims to take learners with little to no programming experience to being able to create MATLAB programs that solve real-world problems in engineering and the sciences. The focus is on computer programming in general, but the numerous language features that make MATLAB uniquely suited to engineering and scientific computing are also covered in depth.

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Python Data Products for Predictive Analytics

Python Data Products for Predictive Analytics

Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course Specialization from UC San Diego. This Specialization is for learners who are proficient with the basics of Python. You’ll start by creating your first data strategy.

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Ethics of Technology

Ethics of Technology

This course explores the ethical implications of data analytics. It connects old ideas – privacy, surveillance, power, justice, accountability, corporate responsibility, stakeholder theory – with new technologies and cases, such as the use of machine learning to predict crime. The course will prepare you to evaluate strategic arguments about the ethics of data analytics and to relate data analytics to ethical concepts so that you approach newer, ambiguous capabilities of technology and artificial intelligence with a critical eye.

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  • 16 ساعات
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Practical Data Science on the AWS Cloud

Practical Data Science on the AWS Cloud

Development environments might not have the exact requirements as production environments. Moving data science and machine learning projects from idea to production requires state-of-the-art skills. You need to architect…

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Interpretable Machine Learning Applications: Part 1

Interpretable Machine Learning Applications: Part 1

In this 1-hour long project-based course, you will learn how to create interpretable machine learning applications on the example of two classification regression models, decision tree and random forestc classifiers. You will also learn how to explain such prediction models by extracting the most important features and their values, which mostly impact these prediction models. In this sense, the project will boost your career as Machine Learning (ML) developer and modeler in that you will be able to get a deeper insight into the behaviour of your ML model.

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Data Science for Investment Professionals

Data Science for Investment Professionals

This Specialization 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 th…

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Interpretable Machine Learning Applications: Part 4

Interpretable Machine Learning Applications: Part 4

In this 1-hour long guided project, you will learn how to use the "What-If" Tool (WIT) in the context of training and testing machine learning prediction models. In particular, you will learn a) how to set up a machine learning application in Python by using interactive Python notebook(s) on Google's Colab(oratory) environment, a.k.a.

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  • 3 ساعات
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Cloud Machine Learning Engineering and MLOps

Cloud Machine Learning Engineering and MLOps

Welcome to the fourth course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will build upon the Cloud computing and data engineering concepts introduced in the first three courses to apply Machine Learning Engineering to real-world projects. First, you will develop Machine Learning Engineering applications and use software development best practices to create Machine Learning Engineering applications. Then, you will learn to use AutoML to solve problems more efficiently than traditional machine learning approaches alone.

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  • 12 ساعات
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Digital Transformation Using AI/ML with Google Cloud

Digital Transformation Using AI/ML with Google Cloud

This series of courses begins by introducing fundamental Google Cloud concepts to lay the foundation for how businesses use data, machine learning (ML), and artificial intelligence (AI) to transform their business models. The specialization is intended for anyone interested in how the use of AI and ML for the cloud, and especially for data, creates opportunities and requires change for businesses. No previous experience with ML, programming, or cloud technologies is required. The courses do not include any hands-on technical training.

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Investment Management with Python and Machine Learning

Investment Management with Python and Machine Learning

The Data Science and Machine Learning for Asset Management Specialization has been designed to deliver a broad and comprehensive introduction to modern methods in Investment Management, with a particular emphasis on the use of data science and machine learning techniques to improve investment decisions.By the end of this specialization, you will have acquired the tools required for making sound investment decisions, with an emphasis not only on the foundational theory and underlying concepts, but also on practical applications and implementation.

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Applied Data Science with Python

Applied Data Science with Python

The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language.

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Machine Learning for Marketing

Machine Learning for Marketing

Understand the structure and techniques used in Machine Learning, Text Mining, and Decision Science for Marketing. Explore the fascinating world of Machine Learning and its transformative applications in marketing. Explain how analytics and decision science approaches for marketing can enhance the quality of marketing decision-making. Foundation in digital marketing analytics to understand the consumer journey, intent, and activity on your business website.

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TensorFlow: Data and Deployment

TensorFlow: Data and Deployment

Continue developing your skills in TensorFlow as you learn to navigate through a wide range of deployment scenarios and discover new ways to use data more effectively when training your machine learning models. In this four-course Specialization, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications.

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Machine Learning Rock Star – the End-to-End Practice

Machine Learning Rock Star – the End-to-End Practice

Machine learning reinvents industries and runs the world. Harvard Business Review calls it “the most important general-purpose technology of our era.” But while there are so many how-to courses for hands-on techies, the…

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Hands-on Foundations for Data Science and Machine Learning with Google Cloud Labs

Hands-on Foundations for Data Science and Machine Learning with Google Cloud Labs

In this Google Cloud Labs Specialization, you'll receive hands-on experience building and practicing skills in BigQuery and Cloud Data Fusion.

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Exploratory Data Analysis in AWS

Exploratory Data Analysis in AWS

Exploratory Data Analysis in AWS is the second course in the AWS Certified Machine Learning Specialty specialization. The main focus of this course is to analyze Data Streams and Data Analytics services in AWS along with exploring Data Analysis in AWS. 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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Explainable deep learning models for healthcare - CDSS 3

Explainable deep learning models for healthcare - CDSS 3

This course will introduce the concepts of interpretability and explainability in machine learning applications. The learner will understand the difference between global, local, model-agnostic and model-specific explanations. State-of-the-art explainability methods such as Permutation Feature Importance (PFI), Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanation (SHAP) are explained and applied in time-series classification.

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  • 30 ساعات
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Business Application of Machine Learning and Artificial Intelligence in Healthcare

Business Application of Machine Learning and Artificial Intelligence in Healthcare

The future of healthcare is becoming dependent on our ability to integrate Machine Learning and Artificial Intelligence into our organizations. But it is not enough to recognize the opportunities of AI; we as leaders in the healthcare industry have to first determine the best use for these applications ensuring that we focus our investment on solving problems that impact the bottom line. Throughout these four modules we will examine the use of decision support, journey mapping, predictive analytics, and embedding Machine Learning and Artificial Intelligence into the healthcare industry.

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  • 13 ساعات
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AI Foundations for Everyone

AI Foundations for Everyone

Artificial Intelligence (AI) is no longer science fiction. It is rapidly permeating all industries and having a profound impact on virtually every aspect of our existence. Whether you are an executive, a leader, an industry professional, a researcher, or a student - understanding AI, its impact and transformative potential for your organization and our society is of paramount importance. This specialization is designed for those with little or no background in AI, whether you have technology background or not, and does not require any programming skills.

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Google Cloud Speech API: Qwik Start

Google Cloud Speech API: Qwik Start

This is a self-paced lab that takes place in the Google Cloud console. The Google Cloud Speech API integrates speech recognition into dev apps; you can now send audio/receive a text transcription. Watch these short videos Powerful Speech Recognition Using Google Machine Learning and Google Cloud Speech: Qwik Start - Qwiklabs Preview

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  • 1 ساعات
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Building Cloud Computing Solutions at Scale

Building Cloud Computing Solutions at Scale

With more companies leveraging software that runs on the Cloud, there is a growing need to find and hire individuals with the skills needed to build solutions on a variety of Cloud platforms. Employers agree: Cloud talent is hard to find.

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