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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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Introduction to Topic Modelling in R

Introduction to Topic Modelling in R

By the end of this project, you will know how to load and pre-process a data set of text documents by converting the data set into a document feature matrix and reducing it’s dimensionality. You will also know how to run an unsupervised machine learning LDA topic model (Latent Dirichlet Allocation). You will know how to plot the change in topics over time as well as explore the distribution of topic probability in each document.

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  • 3 ساعات
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Natural Language Processing

Natural Language Processing

Natural Language Processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence that uses algorithms to interpret and manipulate human language. This technology is one of the most broadly applied areas of machine learning and is critical in effectively analyzing massive quantities of unstructured, text-heavy data.

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Deep Learning

Deep Learning

An introduction to the field of deep learning, including neural networks, convolutional neural networks, recurrent neural networks, transformers, generative models, neural network compression and transfer learning. This course will benefit students’ careers as a machine learning engineer or data scientist.

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AI for Medicine

AI for Medicine

AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This three-course Specialization will give you practical experience in applying machine learning to concrete problems in medicine. These courses go beyond the foundations of deep learning to teach you the nuances in applying AI to medical use cases. If you are new to deep learning or want to get a deeper foundation of how neural networks work, we recommend taking the Deep Learning Specialization.

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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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AI Product Management

AI Product Management

Organizations in every industry are accelerating their use of artificial intelligence and machine learning to create innovative new products and systems. This requires professionals across a range of functions, not just strictly within the data science and data engineering teams, to understand when and how AI can be applied, to speak the language of data and analytics, and to be capable of working in cross-functional teams on machine learning projects. This Specialization provides a foundational understanding of how machine learning works and when and how it can be applied to solve problems.

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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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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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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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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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Machine Learning Implementation and Operations in AWS

Machine Learning Implementation and Operations in AWS

Machine Learning Implementation Operations in AWS is the fifth Course in the AWS Certified Machine Learning Specialty specialization. The course has a major focus on designing and implementing machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance. This course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 1:00-1:30 Hours Video lectures that provide both Theory and Hands -On knowledge.

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  • 6 ساعات
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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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  • 5 ساعات
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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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Data Science: Foundations using R

Data Science: Foundations using R

Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in R, and conducting reproducible research. Learners who complete this specialization will be prepared to take the Data Science: Statistics and Machine Learning specialization, in which they build a data product using real-world data. The five courses in this specialization are the very same courses that make up the first half of the Data Science Specialization.

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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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Achieving Advanced Insights with BigQuery

Achieving Advanced Insights with BigQuery

The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs.

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  • 8 ساعات
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Fundamentals of Machine Learning for Supply Chain

Fundamentals of Machine Learning for Supply Chain

This course will teach you how to leverage the power of Python to understand complicated supply chain datasets. Even if you are not familiar with supply chain fundamentals, the rich data sets that we will use as a canvas will help orient you with several Pythonic tools and best practices for exploratory data analysis (EDA). As such, though all datasets are geared towards supply chain minded professionals, the lessons are easily generalizable to other use cases.

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  • 13 ساعات
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