In this paper, we have discussed initial findings and results of our experiment to predict sexual and reproductive health vulnerabilities of migrants in a data-constrained environment. Notwithstanding the limited research and data about migrants and migration cities, we propose a solution that simultaneously focuses on data gathering from migrants, augmenting awareness of the migrants to reduce mishaps, and setting up a mechanism to present insights to the key stakeholders in migration to act upon. We have designed a webapp for the stakeholders involved in migration: migrants, who would participate in data gathering process and can also use the app for getting to know safety and awareness tips based on analysis of the data received; public health workers, who would have an access to the database of migrants on the app; policy makers, who would have a greater understanding of the ground reality, and of the patterns of migration through machine-learned analysis. Finally, we have experimented with different machine learning models on an artificially curated dataset. We have shown, through experiments, how machine learning can assist in predicting the migrants at risk and can also help in identifying the critical factors that make migration dangerous for migrants. The results for identifying vulnerable migrants through machine learning algorithms are statistically significant at an alpha of 0.05.

If you remember the days of cassette tapes, floppy disks and flip phones, then we don't need to tell you how quickly technology is moving lately. Now it seems we're running headlong into the era of artificial intelligence. Yes, smart computers capable of learning and adapting to solve complex problems. We're not quite to HAL yet, but it seems technology is getting there. And with these new technologies comes a new vocabulary.

This post is a part of my forthcoming book on Mathematical foundations of Data Science. In this post, we use the Perceptron algorithm to bridge the gap between high school maths and deep learning. As part of my role as course director of the Artificial Intelligence: Cloud and Edge Computing at the University..., I see more students who are familiar with programming than with mathematics. They have last learnt maths years ago at University. And then, suddenly they find that they encounter matrices, linear algebra etc when they start learning Data Science.

Based on my experience as a curriculum specialist in the world of digital resources, here's the number one most successful content-sharing best practice of all time: do you have a group chat where you share nonsensical YouTube videos with each other? I'm sure the last thing you shared on it probably wasn't what you think of when you think of the life-changing potential of digital resources, but think of it anyway. Did you save it for later? There's so much that determines whether content "works" for someone, but for a curriculum specialist, whether it did or not is the most important question in the world. That's why I'm fascinated with these group chats and seek them out whenever we, at Learning Equality, visit our users: if they let me, I'll peer over their shoulders to see who's sharing what in Rajasthan (seventh-grade girls, Bollywood music), in Mexico (twentysomethings, stickered selfies), and in Kakuma refugee camp (everyone, hair styles, Office tutorials, conversion rates…).

Teachers learn best from experience, and from each other. Communities of practice are an important opportunity for teachers to continue to refine their teaching, reflect, and learn valuable insights from colleagues and mentors -- whether through discussing their own practice, or hearing about the practice of others. Teachers in low-resource/disconnected environments who want to improve their content-specific pedagogy and general teaching practice, can frequently be cut off from these opportunities. In such environments, teachers may have limited numbers of peers with which to interact, especially for those who are subject specialists. Standard models of teacher development and continual professional development are best delivered through communities of practice, because they allow for engagement in discussions with other teachers, and learning from their experience, in order to improve the quality of lessons for their students.

We explored the need for automated curriculum alignment in crisis contexts, and the possible role of artificial intelligence (AI) in recognizing curricular mandates and patterns, and recommending pertinent educational content in return. This work is part of a broader collaboration working with refugees and partner organizations to explore utilizing digital education to support learning in these contexts. The Design2Align series has included discussion of contextual display and creation of metadata, teacher-generated content annotations, and the technical considerations in OER for curriculum alignment facilitation. We're delighted to introduce the fourth installment of the blog series by our co-founder and Executive Director, Jamie Alexandre. Jamie discusses how user data from multiple open platforms could be used to train machine learning models, in order to optimize recommendations to teachers of contextually relevant learning pathways for their students. Our table brought together participants from diverse backgrounds and skill sets, spanning government, foundations, the tech industry, education nonprofits, and UN agencies, which made for some lively debates!

We explored the need for automated curriculum alignment in crisis contexts, and the possible role of artificial intelligence (AI) in recognizing curricular mandates and patterns, and recommending pertinent educational content in return. This work is part of a broader collaboration working with refugees and partner organizations to explore utilizing digital education to support learning in these contexts. The experience of engaging our professional communities in such a challenging question was as valuable as the outputs themselves, so we've been sharing the discussions and debates we've had as they may be useful in other's work. Over the past month, the Design2Align blog post series has covered topics such as contextual display and creation of metadata, teacher-generated content annotations, technical considerations in OER for curriculum alignment facilitation, and open models for just-in-time learning pathway recommendations. Today, Learning Equality's UX Design Lead, Jessica Aceret talks about the specific curriculum needs for crisis contexts, and how it requires not only a human touch but also an alignment tool that provides intelligent content recommendations so that the relevant resources can be more easily found. The Design Sprint on Curriculum Alignment in Crisis Contexts, which took place back in March, in Paris, saw many different roles in the education technology space strategically brought together -- curriculum designers, policymakers, technology experts, refugees, and more.

Consider a refugee population coming from country C residing in host country B, with limited or no access to education. The trauma of conflict and displacement, coupled with the difficulty of integration within the host country puts refugee populations at a significant educational disadvantage, so it is worthwhile considering options that could "level the playing field" by providing improved access to education. There is hope that the vast amounts of Open Educational Resources (OER) that are freely available on the internet can play a role in this, in particular in combination with educational platforms like Kolibri. The Kolibri platform aims to provide access to learning opportunities for all and it is particularly suited for the refugee context as the runs-anywhere capabilities of the Kolibri applications allow it to be accessed in computer labs, in the classroom, from phones, and in informal learning centres. Our experience and work with partners like UNHCR have shown that in emergency and crisis contexts, a key bottleneck is the lack of sufficient educational content aligned to the learning goals of the project.

They are engaging on social media and chatbots. Find out what you need to do to reach them effectively. Guest: Mary has been nicknamed the "ChatBotMom" by her Messenger Marketing community, and her innovative development of chatbot copywriting has helped her students and clients sell millions in products, services and online courses. IN 100 words or less, what is your chatbot or AI Voice app and why? Guest – books, Seth Godin's "This is Marketing" and Mark Schaeffer's "Marketing Rebellion" Convert long, story emails into interactive chat conversations to help your bot engage with subscribers and convert.

The advent of cloud-based computing servers, smart sensors that can communicate seamlessly over wireless networks, and advances in the field of data analytics means that artificial intelligence (AI) is more accessible to the mining sector than ever before and miners are beginning to see a return on investment.