Data poisoning is a type of adversarial attack on training data where an attacker manipulates a fraction of data to degrade the performance of machine learning model. Therefore, applications that rely on external data-sources for training data are at a significantly higher risk. There are several known defensive mechanisms that can help in mitigating the threat from such attacks. For example, data sanitization is a popular defensive mechanism wherein the learner rejects those data points that are sufficiently far from the set of training instances. Prior work on data poisoning defense primarily focused on offline setting, wherein all the data is assumed to be available for analysis. Defensive measures for online learning, where data points arrive sequentially, have not garnered similar interest. In this work, we propose a defense mechanism to minimize the degradation caused by the poisoned training data on a learner's model in an online setup. Our proposed method utilizes an influence function which is a classic technique in robust statistics. Further, we supplement it with the existing data sanitization methods for filtering out some of the poisoned data points. We study the effectiveness of our defense mechanism on multiple datasets and across multiple attack strategies against an online learner.

In educational applications, Knowledge Tracing (KT), the problem of accurately predicting students' responses to future questions by summarizing their knowledge states, has been widely studied for decades as it is considered a fundamental task towards adaptive online learning. Among all the proposed KT methods, Deep Knowledge Tracing (DKT) and its variants are by far the most effective ones due to the high flexibility of the neural network. However, DKT often ignores the inherent differences between students (e.g. memory skills, reasoning skills, ...), averaging the performances of all students, leading to the lack of personalization, and therefore was considered insufficient for adaptive learning. To alleviate this problem, in this paper, we proposed Leveled Attentive KNowledge TrAcing (LANA), which firstly uses a novel student-related features extractor (SRFE) to distill students' unique inherent properties from their respective interactive sequences. Secondly, the pivot module was utilized to dynamically reconstruct the decoder of the neural network on attention of the extracted features, successfully distinguishing the performance between students over time. Moreover, inspired by Item Response Theory (IRT), the interpretable Rasch model was used to cluster students by their ability levels, and thereby utilizing leveled learning to assign different encoders to different groups of students. With pivot module reconstructed the decoder for individual students and leveled learning specialized encoders for groups, personalized DKT was achieved. Extensive experiments conducted on two real-world large-scale datasets demonstrated that our proposed LANA improves the AUC score by at least 1.00% (i.e. EdNet 1.46% and RAIEd2020 1.00%), substantially surpassing the other State-Of-The-Art KT methods.

Roorkee: Indian Institute of Technology (IIT) Roorkee has launched two online certificate programs in high-demand topics -- Data Science and Machine Learning and Advanced Machine Learning and AI -- on Coursera, one of the world's leading online learning platform. "We are happy to announce two certificate courses in data science, machine learning, and AI in partnership with Coursera. This will enable a large number of aspirants to acquire these relevant areas for their professional growth," said Prof. Ajit K. Chaturvedi, Director, IIT Roorkee IIT Roorkee is among 150 top universities, including Yale, University of Michigan, University of Pennsylvania, and Imperial College of London -- that offer programs on Coursera. "For over 170 years, IIT Roorkee has been a leading Indian institution, known for its rigorous technical programs," said Betty Vandenbosch, Chief Content Officer at Coursera. "Through our partnership, we are expanding access and allowing more students to learn from IIT Roorkee's renowned faculty. Learners will gain the cutting-edge skills they need to advance their careers while creating powerful networks with their peers."

Artificial intelligence has entered every industry, and the educational sector is no exception. The administrative staff, management, teachers, and students are all using AI in different ways to achieve similar goals. During the last few years, AI has spread its roots much wider and deeper in this sector. Markets and Markets has predicted that the global market share of AI in education is estimated to reach $3.68 billion by 2023 at a CAGR (Compound Annual Growth Rate) of 47%. Another platform, Market Search Engine, has predicted that the share will reach $5.80 billion by 2025.

Udacity is one of the most popular MOOC-based e-learning platforms in the world. Udacity has a wide range of machine learning and data science courses. Some are free and some are paid. But in this article, I am gonna discuss all the Udacity FREE Courses on Machine Learning and Data Science. For these courses, You don't need to pay a single buck.

With the current pandemic accelerating the revolution of AI in healthcare, where is the industry heading in the next 5-10 years? What are the key challenges and most exciting opportunities? To answer those questions, DeepLearning.AI and Stanford Institute for Human-Centered Artificial Intelligence (HAI) are proud to present our virtual event, Healthcare's AI Future: A Conversation with Fei-Fei Li & Andrew Ng, at 10am PT on April 29. What's special about this event is that you get to decide what our speakers talk about. If you'd like to submit and upvote questions for our speakers, please sign up for the Q&A General access ticket.

Personalization and active learning are key aspects to successful learning. These aspects are important to address in intelligent educational applications, as they help systems to adapt and close the gap between students with varying abilities, which becomes increasingly important in the context of online and distance learning. We run a comparative head-to-head study of learning outcomes for two popular online learning platforms: Platform A, which follows a traditional model delivering content over a series of lecture videos and multiple-choice quizzes, and Platform B, which creates a personalized learning environment and provides problem-solving exercises and personalized feedback. We report on the results of our study using pre- and post-assessment quizzes with participants taking courses on an introductory data science topic on two platforms. We observe a statistically significant increase in the learning outcomes on Platform B, highlighting the impact of well-designed and well-engineered technology supporting active learning and problem-based learning in online education. Moreover, the results of the self-assessment questionnaire, where participants reported on perceived learning gains, suggest that participants using Platform B improve their metacognition.

spaCy is a modern Python library for industrial-strength Natural Language Processing. In this free and interactive online course, you'll learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

With COVID-19 taking hold over the world, it compelled associations worldwide to reevaluate how they conduct business, train, and prepare their employees to address the disruption and business elements' difficulties. How are associations preparing for the coming year in reskilling and upskilling their employees? The pandemic has made unprecedented difficulties that have constrained organizations to search for alternative work types like work from home or remote working and carry virtual training to the front. Prior virtual training was utilized uniquely for the remote workforce or individuals spread across geographies. Working from home is the new normal at this point.

Are you looking to land a top-paying job in Data Science? Or are you a seasoned AI practitioner who want to take your career to the next level? Or are you an aspiring data scientist who wants to get Hands-on Data Science and Artificial Intelligence? If the answer is yes to any of these questions, then this course is for you! Data Science is one of the hottest tech fields to be in right now! The field is exploding with opportunities and career prospects.