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Our Courses
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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Course by
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Self Paced
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English
Build, Train, and Deploy ML Pipelines using BERT
In the second course of the Practical Data Science Specialization, you will learn to automate a natural language processing task by building an end-to-end machine learning pipeline using Hugging Face’s highly-optimized implementation of the state-of-the-art BERT algorithm with Amazon SageMaker Pipelines. Your pipeline will first transform the dataset into BERT-readable features and store the features in the Amazon SageMaker Feature Store.
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Course by
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Self Paced
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10 hours
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English
ChatGPT Teach-Out
This Teach-Out introduces learners to artificial intelligence and explains how large language models and chatbots like ChatGPT work. You will better understand the ethical use of artificial intelligence, the implications of authorship, and how tools like ChatGPT might be utilized and regulated moving forward. ChatGPT launched in November 2022 in an effort to enhance natural language processing tasks like translation, text summarization, and text generation. Within five days of release, ChatGPT crossed 1 million users.
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Self Paced
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6 hours
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English
AI and Disaster Management
In this course, you will be introduced to the four phases of the disaster management cycle; mitigation, preparation, response, and recovery. You’ll work through two case studies in this course. In the first, you will use computer vision to analyze satellite imagery from Hurricane Harvey in 2017 to identify damage in affected areas. In the second, you will use natural language processing techniques to explore trends in aid requests in the aftermath of the 2010 earthquake in Haiti.
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Self Paced
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12 hours
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English
Deploy Bridgerton NLP SMS Text Generator
Welcome to the “Deploy Bridgerton NLP SMS Text Generator” guided project. In this project, we will deploy an NLP text generator model that sends text messages of generated words to a phone number via SMS through a python Streamlit app. The model has been trained on quotes from Netflix's popular tv show "Bridgerton". This project is an intermediate python project for anyone interested in learning about how to productionize natural language text generator models as a Streamlit app on Heroku and leveraging python modules to send SMS texts.
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Self Paced
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2 hours
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English
Assessment for Learning
For several decades now, assessment has become an increasingly pressing educational priority. Teacher and school accountability systems have come to be based on analysis of large-scale, standardized summative assessments. As a consequence, assessment now dominates most conversations about reform, particularly as a measure of teacher and school accountability for learner performance. Behind the often heated and at times ideologically gridlocked debate is a genuine challenge to address gaps in achievement between different demographically identifiable groups of students.
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Course by
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Self Paced
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14 hours
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English
JSON and Natural Language Processing in PostgreSQL
Within this course, you’ll learn about how PostgreSQL creates and uses inverted indexes for JSON and natural language content. We will use various sources of data for our databases, including access to an online API and spidering its data and storing the data in a JSON column in PostgreSQL. Students will explore how full-text inverted indexes are structured. Students will build their own inverted indexes and then make use of PostgreSQL built-in capabilities to support full-text indexes.
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Self Paced
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16 hours
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English
Computational Social Science
For more information please view the Computational Social Science Trailer Digital technology has not only revolutionized society, but also the way we can study it. Currently, this is taken advantage of by the most valuable companies in Silicon Valley, the most powerful governmental agencies, and the most influential social movements. What they have in common is that they use computational tools to understand, and ultimately influence human behavior and social dynamics. An increasing part of human interaction leaves a massive digital footprint behind.
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Self Paced
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English
Fine Tune BERT for Text Classification with TensorFlow
This is a guided project on fine-tuning a Bidirectional Transformers for Language Understanding (BERT) model for text classification with TensorFlow. In this 2.5 hour long project, you will learn to preprocess and tokenize data for BERT classification, build TensorFlow input pipelines for text data with the tf.data API, and train and evaluate a fine-tuned BERT model for text classification with TensorFlow 2 and TensorFlow Hub.
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Self Paced
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3 hours
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English
AI Workflow: Machine Learning, Visual Recognition and NLP
This is the fourth course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. Course 4 covers the next stage of the workflow, setting up models and their associated data pipelines for a hypothetical streaming media company. The first topic covers the complex topic of evaluation metrics, where you will learn best practices for a number of different metrics including regressi
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Self Paced
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14 hours
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English
TensorFlow: Advanced Techniques
About TensorFlow TensorFlow is an end-to-end open-source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML, and developers easily build and deploy ML-powered applications. TensorFlow is commonly used for machine learning applications such as voice recognition and detection, Google Translate, image recognition, and natural language processing. About this Specialization Expand your knowledge of the Functional API and build exotic non-sequential model types.
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Self Paced
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English
Natural Language Processing and Capstone Assignment
Welcome to Natural Language Processing and Capstone Assignment. In this course we will begin with an Recognize how technical and business techniques can be used to deliver business insight, competitive intelligence, and consumer sentiment. The course concludes with a capstone assignment in which you will apply a wide range of what has been covered in this specialization.
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5 hours
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English
JSON and Natural Language Processing in PostgreSQL
In this third course in PostgreSQL for Everybody, learners will learn how PostgreSQL creates and uses JSON and natural language content. Learners will explore using multiple sources of data and how text is structured within PostgreSQL.
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English
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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Self Paced
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English
Natural Language Processing in Microsoft Azure
Natural language processing supports applications that can see, hear, speak with, and understand users. Using text analytics, translation, and language understanding services, Microsoft Azure makes it easy to build applications that support natural language. In this course, you will learn how to use the Text Analytics service for advanced natural language processing of raw text for sentiment analysis, key phrase extraction, named entity recognition, and language detection. You will learn how to recognize and synthesize speech by using Azure Cognitive Services.
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8 hours
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English
Artificial Intelligence on Microsoft Azure
Whether you're just beginning to work with Artificial Intelligence (AI) or you already have AI experience and are new to Microsoft Azure, this course provides you with everything you need to get started.
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Self Paced
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4 hours
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English
Tweet Emotion Recognition with TensorFlow
In this 2-hour long guided project, we are going to create a recurrent neural network and train it on a tweet emotion dataset to learn to recognize emotions in tweets. The dataset has thousands of tweets each classified in one of 6 emotions. This is a multi class classification problem in the natural language processing domain. We will be using TensorFlow as our machine learning framework. You will need prior programming experience in Python.
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Self Paced
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3 hours
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English
Select Topics in Python: Natural Language Processing
Code and run your first NLP program in minutes without installing anything! This course is designed for learners who have some experience with Python but are a novice to NLP. The modules in this course cover processing and analyzing text; analyzing speech, syntax, and semantics; and building a chatbot. To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing.
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Self Paced
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7 hours
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English
Amazon Echo Reviews Sentiment Analysis Using NLP
In this hands-on project, we will predict customer sentiment using natural language processing techniques.
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Self Paced
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2 hours
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English
Create a Superhero Name Generator with TensorFlow
In this guided project, we are going to create a neural network and train it on a small dataset of superhero names to learn to generate similar names. The dataset has over 9000 names of superheroes, supervillains and other fictional characters from a number of different comic books, TV shows and movies. Text generation is a common natural language processing task. We will create a character level language model that will predict the next character for a given input sequence.
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Self Paced
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3 hours
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English
Introduction to Deep Learning
Deep Learning is the go-to technique for many applications, from natural language processing to biomedical. Deep learning can handle many different types of data such as images, texts, voice/sound, graphs and so on. This course will cover the basics of DL including how to build and train multilayer perceptron, convolutional neural networks (CNNs), recurrent neural networks (RNNs), autoencoders (AE) and generative adversarial networks (GANs).
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Course by
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Self Paced
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60 hours
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English
Introduction to Artificial Intelligence (AI)
Artificial Intelligence (AI) is all around us, seamlessly integrated into our daily lives and work. Enroll in this course to understand the key AI terminology and applications and launch your AI career or transform your existing one. This course covers core AI concepts, including deep learning, machine learning, and neural networks. You’ll examine generative AI models, including large language models (LLMs) and their capabilities.
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Self Paced
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9 hours
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English
Building a unique NLP project: 1984 book vs 1984 album
Welcome to the “Building a unique NLP project: 1984 book vs 1984 album” guided project. This project is for anyone interested in exploring fun and interactive Natural Language Processing (NLP) projects. Inspired by the cultural phenomenon, Versus, in this project we’re going to be leveraging the NLP to compare 1984, the dystopian social science fiction novel by the English novelist George Orwell and 1984, the sixth studio album by American rock band Van Halen. In this project, we’ll explore the NLP techniques of: 1. summarizing text 2. sentiment analysis 3.
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Course by
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Self Paced
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3 hours
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English
Transfer Learning for NLP with TensorFlow Hub
This is a hands-on project on transfer learning for natural language processing with TensorFlow and TF Hub.
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Course by
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Self Paced
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2 hours
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English