Many machine learning models have been built to tackle information overload issues on Massive Open Online Courses (MOOC) platforms. These models rely on learning powerful representations of MOOC entities. However, they suffer from the problem of scarce expert label data. To overcome this problem, we propose to learn pre-trained representations of MOOC entities using abundant unlabeled data from the structure of MOOCs which can directly be applied to the downstream tasks. While existing pre-training methods have been successful in NLP areas as they learn powerful textual representation, their models do not leverage the richer information about MOOC entities. This richer information includes the graph relationship between the lectures, concepts, and courses along with the domain knowledge about the complexity of a concept. We develop MOOCRep, a novel method based on Transformer language model trained with two pre-training objectives : 1) graph-based objective to capture the powerful signal of entities and relations that exist in the graph, and 2) domain-oriented objective to effectively incorporate the complexity level of concepts. Our experiments reveal that MOOCRep's embeddings outperform state-of-the-art representation learning methods on two tasks important for education community, concept pre-requisite prediction and lecture recommendation.

Data science courses contain math--no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time. Science is undergoing a data explosion, and astronomy is leading the way. Modern telescopes produce terabytes of data per observation, and the simulations required to model our observable Universe push supercomputers to their limits.

Artificial Intelligence is finally here and most of us are already actively using it in our day-to-day life (even without knowing it). To prepare our future generation in order to harness these technologies, people need to understand how they can use AI first of all! Only then can they use it to facilitate learning and solve real-world problems. The course is aimed at all those people, irrespective of their profession, who would like to learn how to make active use of AI. No prior knowledge is assumed, no expertise in any related area is required because we will start by introducing the very basic concepts.

Goto: Amazon DynamoDB: Building NoSQL Database-Driven ApplicationsThis course introduces you to NoSQL databases and the challenges they solve. Expert instructors will dive deep into Amazon DynamoDB topics such as recovery, SDKs, partition keys, security and encryption, global tables, stateless applications, streams, and best practices. DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It's a fully managed, multiregion, multimaster database with built-in security, backup and restore, and in-memory caching for internet-scale applications. DynamoDB can handle more than 10 trillion requests per day and support peaks of more than 20 million requests per second.

In this project-based course, you are going to build an end-to-end machine learning pipeline in Azure ML Studio, all without writing a single line of code! This course uses the Adult Income Census data set to train a model to predict an individual's income. It predicts whether an individual's annual income is greater than or less than $50,000. The estimator used in this project is a Two-Class Boosted Decision Tree classifier. Some of the features used to train the model are age, education, occupation, etc.

In this section, we will learn about the course structure and the meaning of some key terms associated with HR Analytics.

The DeepLearning.AI TensorFlow: Advanced Techniques Specialization introduces the features of TensorFlow that provide learners with more control over their model architecture, and gives them the tools to create and train advanced ML models. This Specialization is for early and mid-career software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models.

Do you feel overwhelmed going through all the AI and Machine learning study materials? These Machine learning and AI projects will get you started with the implementation of a few very interesting projects from scratch. The first one, a Web application for Object Identification will teach you to deploy a simple machine learning application. The second one, Dog Breed Prediction will help you building & optimizing a model for dog breed prediction among 120 breeds of dogs. This is built using Deep Learning libraries.

The analytics leader of a US-based Fortune 200 company was under severe pressure. Her team supported 45,000 employees of the global energy company, and the business users weren't happy. The analytics deliverables were often late and suffered from poor quality. The analytics team was a part of the IT organization and was struggling to fill their open positions. The skills needed couldn't be found within the IT team.

IIT Madras has invited applications for a free online course called Introduction to Machine Learning on the NPTEL platform. The course, which is AICTE FDP approved, can be taken by senior undergraduate or postgraduate students pursuing their BE, MS, ME or even PhD. The course is 12 weeks long and will be conducted from 26 July to 15 October 2021. It would be most beneficial for students pursuing education in the domains of computer science and engineering, artificial intelligence, data science, programming and robotics. The course will be conducted by professor Balaraman Ravindran who is associated with the department of computer science at the Indian Institute of Technology Madras and is also a Mindtree Faculty Fellow.