Here are the top 5 PHP frameworks that every developer should learn:

1. Laravel

Laravel is a powerful, full-stack PHP framework with a great community and a focus on elegance and simplicity. It is a popular choice for web development projects of all sizes, from small blogs to large enterprise applications. Laravel is known for its expressive syntax, powerful features, and large ecosystem of libraries and packages.

2. Symfony

Symfony is another popular PHP framework with a strong focus on modularity and flexibility. It is the foundation for many other PHP frameworks, including Drupal and Magento. Symfony is a good choice for developers who need a framework that is highly customizable and can be adapted to a wide range of projects.

3. Yii

Yii is a high-performance PHP framework that is known for its speed and scalability. It is a good choice for developers who need to build web applications that can handle a lot of traffic. Yii is also a good choice for developers who are looking for a framework with a large and active community.

4. CodeIgniter

CodeIgniter is a lightweight PHP framework that is easy to learn and use. It is a good choice for developers who are just starting out with PHP or who need to build a simple web application quickly. CodeIgniter is also a good choice for developers who are looking for a framework with a small footprint.

5. Slim

Slim is a micro-framework that is designed to be as small and simple as possible. It is a good choice for developers who need to build small, RESTful APIs or web applications. Slim is also a good choice for developers who are looking for a framework that is easy to learn and use.

These are just a few of the many great PHP frameworks that are available. The best framework for you will depend on your specific needs and preferences.

The post The Top 5 PHP Frameworks Every Developer Should Learn appeared first on Artificial Intelligence.

Data Science Coding Schools to help to launch a career in Data Science

In recent years, the scope for data science has been gaining momentum with large amounts of data being produced across the globe. This also increases the opportunities for data scientists and enthusiasts who can process and analyze data for new insights. The Bureau of Labour Statistics of the U.S estimates a 15% increase in the demand for trained data scientists over the next decade due to meet the data requirements. This means completing a data science course could benefit you to break into this highly in-demand field which can boost your career to a great extent. Data science courses can not only help you in getting a job but also ensures you stay in the field for a longer time. Here are the top 10 data science coding schools to help you launch a career in data science. Let’s quickly jump into the article to know more about them.

• BOOST YOUR CAREER: 10 BEST DATA SCIENCE BOOTCAMP FOR 2021
• TOP 6 ONLINE DATA SCIENCE COURSES TO WATCH OUT FOR IN 2021
• FOR AMATEURS: BEST DATA SCIENCE COURSES FOR BEGINNERS IN 2021

1. Propulsion Academy

Learning mode: Online and Offline (Munish, Zurich)

Propulsion Academy provides opportunities to learn about the new technologies, tools, and techniques that are necessary to master all areas of data science from scratch. This academy offers data science courses such as Data Science Bootcamp full-time, Data Science Bootcamp part-time dealing with subjects like Back-End Development, Blockchain, Cryptography, CSS, R, Python, Machine Learning, Coding, and natural language processing. Students can apply this knowledge and skills in the real world with its industrial-based projects. The academy also offers career assistance in terms of jobs and careers.

2. NYC Data Science Academy

Learning mode: Online and Offline (NYC)

The NYC Data science academy promotes three courses: online Bootcamp, a Remote-Live Bootcamp, and a professional development course. The Online Bootcamp is of both full-time and part-time, remote Bootcamp is a full-time course and professional development is also a full-time course. The subjects of the academy include Data Science, Data Visualization, Git, Hadoop, Linux, Coding, and Python.

3. Data Science Retreat

Learning mode: Offline (Berlin)

Data science retreat offers full-time data science immersive courses. The subjects include Big Data, Data Science, Machine Learning, Python, Tensorflow, and many more. Once the courses are completed, graduates will have projects that are presented to prospective employers. Career coaching services include resume assistance, practice interviews, and LinkedIn updates.

4. Cambridge Spark Ltd

Learning mode: Offline (Cambridge, London)

Cambridge Spark Ltd offers many applied data science coding courses. The subjects include Data Science, Hadoop, Machine Learning, Python, Coding, etc. It has 14-months blended courses in Data Science and AI. Targeted at offices and currently working professionals, the program simulates real-world projects with Cambridge Spark’s K.A.T.E. (Knowledge assessment teaching engine) platform.

5. Hackwagon Academy

Learning mode: Offline (Singapore)

Hackwagon Academy offers many data science courses with unique subjects such as CSS, Cyber Security, Data Science, Data Visualization, HTML, Python, R, etc. There are three intensive courses provided by the academy: Data Science 101, Data Science 102, and Data Science 103. In Data Science 101, students learn about programming concepts, in 102, students learn about machine learning and python coding. In Data Science 103 they learn about end-to-end Analytics.

6. Galvanize

Learning mode: Online and Offline (Austin, Denver, Los Angeles, NYC, San Francisco)

Galvanize offers full-time courses, part-time courses, and online prep data science courses. The full-time courses run for 13 weeks. It also offers online programming courses. The different types of courses are Data Science Immersive, Data science Prep, Data Science Analytics Online immersive. The subjects include Big Data, CSS, Data Analytics, Data Mining, Data Science, Coding, Python, etc.

7. Ubiqum Code Academy

Learning mode: Online and Offline (Barcelona, Geneva, Madrid)

Ubiqum, Code Academy offers many immersive data science courses. They have campuses in Amsterdam, Barcelona, Berlin, Lisbon, and Madrid. The courses contain subjects such as AJAX, Algorithms, AWS, Big Data, Python coding, and many more. Students have both full-time and part-time courses and can learn data mining in both R language and Python.

8. Xccelerate

Learning mode: Offline (Hong Kong)

Xccelerate, offers many data science courses such as data science, machine learning, python crash courses both full time and part time. The subjects include AJAX, artificial intelligence, blockchain, and crypto, CSS Coding, Python, and many more.

9. BrainStation

Learning mode: Online and Offline (Boston, Chicago, London, Miami, NYC)

BrainStation, provides both full-time online and offline courses on the campuses. The courses the academy offers are Data Analytics Certification course, Data Science Diploma, and Coding. The subjects include A/B Testing, Agile, Algorithms, API, iOS Development, Python Programming, and many more. Students will be assisted in the career too after completing their courses such as helping them in adding LinkedIn portfolios and resumes, etc.

10. The Dev Masters

Learning mode: Offline (Irvine, Lacey, Los Angeles, San Diego, Santa Monica)

Dev Masters provides numerous data science courses such as Mastering Applied Data Science, Data Science for Professionals, Mastering Applied Data Science with Deep Learning, Coding, and many more. The subjects include Artificial Intelligence, Big Data, Data Science, Machine Learning, and Python coding. The academy is intensive along with part-time and full-time courses.

The post TOP 10 DATA SCIENCE CODING SCHOOLS FOR BOOSTING YOUR CAREER appeared first on Artificial Intelligence.

It introduces from 2021-22 academic session coding for class VI-VII and data science for class VIII-XII in tie-up with Microsoft.

The Central Board of Secondary Education (CBSE) on Friday collaborated with Microsoft to introduce Coding for class VI-VII and Data Science curriculum for class VIII-XII as new skilling subjects in the 2021-2022 academic session to promote and develop skills among school students.

“Under the National Education Policy (NEP)2020, we promised to introduce coding and data science in schools. Today, I’m happy to see CBSE fulfilling the promise right in the session of yr 2021 itself. In association with Microsoft, CBSE is empowering India’s future generations with new-age skills,” said Ramesh Pokhriyal, Education Minister.

Coding and Data Science Curriculum are focused on building critical thinking, computational skills, problem-solving skills, creativity and hands-on exposure to new technologies. In keeping with the NEP 2020, the introduction of these courses aims to build next-generation skills in students.

“As we transition to a world that relies increasingly on technology, it is critical that we impart skills that prepares students and educators across the country to succeed in this digital world. The new course curriculum on coding and data science that we have developed in partnership with Microsoft will equip students with future-ready learning skills. This is an important step to enable self-reliance in our students and equip them with skills like problem-solving, logical thinking, collaboration and design thinking that are critical for success,” Manoj Ahuja, Chairman, CBSE.

Skill modules

Currently, the board offers nine skill modules at the middle school level, 18 skill subjects at secondary level and 38 skill subjects at the senior secondary level to upgrade the proficiency and skills of the young generation and explore the various options available. According to CBSE, more than 20 lakh students are presently studying skill subjects at secondary and senior secondary level in approximately 12,000 schools.

“Skills like coding and data science are the currency of the future. Including these skills in school curriculum will play a strong role in preparing India’s future workforce for the new world of work. We are deeply committed to empowering the students of today to create the world of tomorrow and our partnership with CBSE is a strong step in that direction,” Navtez Bal, Executive Director, Public Sector, Microsoft India.

Microsoft has designed supplementary handbooks in both coding and data science, aligned with NCERT patterns and structures. and cover real-life examples aimed at building exposure to the ethical dimensions exposure to Microsoft Make Code an open-source platform that will enable students to learn better in a gamified manner across all disciplines, including mathematics, languages, and social sciences while it builds the foundation for AI based applications of data science.

“To give an impetus to Skill Education to schools, it has been decided by the CBSE to waive off the application fee for introducing new skill subjects at Senior Secondary Level. Thus schools desirous of introducing new skill subjects in Class XI, can do so without submitting any fee to CBSE effective from the date of release of this circular,” said the CBSE official statement.

The post CBSE to introduce coding, data science in curriculum appeared first on Artificial Intelligence.

The year 2020: what an absolute doozy. Hopefully, your job is steady despite the circumstances — and cutting it for you in terms of wage and fulfillment. But if that’s not the case, you may need to beef up your CV a little to make it shine for (better paying) potential employers.

If you’ve got your heart set on a lucrative position in tech as a web developer, here’s something to get you started: the 2020 Ultimate Web Developer and Design Bootcamp Bundle. This in-depth training packs 11 courses on a wide array of tools and languages, so you can learn them all or poke around to focus on just the specialties you’re pursuing. At just £30.98, it’s worth it for even just a few of the courses.

The Complete 2020 HTML5 CSS3 Course with Flexbox, Grid, and SASS — This course is called the “Golden Introduction to Web Development” because it teaches you about the structure of a webpage, building with HTML5, and stylising with CS33 so you can confidently design, code, and launch websites at the professional level.

Modern Web Design Complete HTML and CSS — Take your skills up a notch with this course, which covers everything you need to know about front-end web design in HTML5, CSS3, and JavaScript.

The Ultimate HTML Developer — If you want to be a web developer, you’re going to have to get acquainted with HTML. This deep dive will teach you how to write HTML from scratch so you can forget about that CS degree.

Build Responsive Real-World Websites with CSS3 v2.0 — Consider this class your personal CSS masterclass, complete with an e-book and interactive tools.

Create an 8-Bit Style Website — This fun course allows you to create a retro-style 8-bit website to get familiar with portfolio and hobby sites.

Understanding APIs and RESTful APIs Crash Course — By the end of this class, you’ll know the ins and outs of APIs and how computers communicate, so you don’t have to pretend to know what’s going on in team meetings.

JavaScript for Beginners: Learn with 6 Main Projects — Often, Java courses only teach you the programming side of Java. But the truth is, JavaScript is an interactive programming language and you have to get to grips with the interactive side at some point.

Git Essentials: The Step-by-Step Guide to Git and GitHub Mastery — Git is the secret tool among developers since it is so widespread. There are a host of commands you’ll use every day in your new workflow, which are all covered in this course.

JavaScript Essentials — JavaScript fundamentals time. Get fluent in variables, query selectors, functions, and much much more in this course. This training is specially designed to give you transferable programming skills so you can become a full stack developer.

Python for Everybody: The Ultimate Python 2 Bootcamp — Python isn’t called the language that can “do it all” for nothing. Set yourself up for success in every Python-related industry with this one.

Web Design JavaScript Front-End Code Course — This course covers how to select elements from the web page with JavaScript. With mini-projects, you can practice making your website shine.

With 11 courses and over 69 hours of content, you can’t go wrong with the 2020 Ultimate Web Developer and Design Bootcamp Bundle, which is on sale for £30.98 for a limited time.

The post Start a new career with this 11-course coding bootcamp appeared first on Artificial Intelligence.

While deep learning is viewed as a small part of the field of artificial intelligence, it’s now a field that is by all accounts growing out of the AI space itself. Deep learning is the advancement of ‘thinking’ computer systems, called neural networks, and using it requires coding procedures unfamiliar to old-school developers. With the assistance of deep learning, we can show our computers to learn for themselves such that it gives us noteworthy outcomes. Furthermore, you get the opportunity to be at the front line, as experts in profound learning are required now like never before.

If you want to learn deep learning and don’t know where to start, we’ve compiled a list of free online courses that can help you learn deep learning.

Creative Applications of Deep Learning with TensorFlow

This course covers the essential segments of deep learning. What it implies, how it works, and creating necessary code to build different algorithms, for example, deep convolutional networks, variational autoencoders, generative adversarial networks, and recurrent neural networks. A significant offering of this course will be to not just see how to build the fundamental segments of these algorithms, yet in addition how to apply them for exploring creative applications. Free and paid choices are available.

Best Deep Learning Course (deepLearning.ai)

This is without a doubt one of the best deep learning affirmations with Andrew Ng himself teaching the subject. The Co-Founder of Global Learning Platform Coursera, Andrew has been the head of Google Brain and Baidu AI group before. Going along with him are teachers from leading institutes like Stanford. In this certification course, you will find out about the foundations of Deep Learning, realize how to build neural networks and understand about machine learning ventures. There will be real time case studies including sign language reading, music generation and natural language processing among others. Alongside all the theory, you will be educated to implement these ideas in Python and TensorFlow.

Deep Learning for Business by Yonsei University

Offered by Yonsei University, Deep Learning for Business shows the nuts and bolts of deep learning and how to implement it in your organization to accelerate outcomes. You will learn how to make business strategies that encourage technical planning on new machine learning and deep learning products.

The course starts with an overview of deep learning products and services, trailed by a module on business with deep learning and machine learning. It additionally covers deep learning Computing Systems and Software, deep learning Neural Networks and deep learning with CNN and RNN. The course finishes with a module on TensorFlow Playgrounds. There’s no expense to learn and you can finish the course in 8 hours.

Deep Learning Certification by IBM (edX)

All through this expert certificate program, you will learn and gain pro Deep Learning abilities through a series of hands-on tasks and projects. Accessible on famous elearning stage edX, the course will come full circle into a Deep Learning capstone project that will help you grandstand your applied abilities to prospective employers. In addition to other things, you will learn central ideas of Deep Learning, including different Neural Networks for both supervised and unsupervised learning. You will likewise figure out how to build and send various types of Deep Architectures including Convolutional Networks, Recurrent Networks just as Autoencoders.

Introduction to Deep Learning by the National Research University Higher School of Economics

Prologue to Deep Learning is the initial segment of the Advanced Machine Learning Specialization from the National Research University Higher School of Economics. It’s intended to assist you with understanding the basics of current neural networks and their application in computer vision and natural language.

The class incorporates video talks, readings and tests. It comprises of 5 modules:

• Introduction to optimization
• Deep learning for images
• Introduction to neural networks
• Deep learning for sequences
• Unsupervised representation learning

You will likewise be entrusted with finishing a task to showcase what you learned in the course.

Complete Guide to TensorFlow for Deep Learning Training with Python (Udemy)

Jose Marcial Portilla has a MS from Santa Clara University and has been teaching Data Science and programming for various years now. His Tensorflow Certification will assist you with figuring out how to utilize Google’s Deep Learning Framework – TensorFlow with Python. He will likewise show you how you can utilize TensorFlow for Image Classification with Convolutional Neural Networks, how to do time series analysis with Recurrent Neural Networks and instruct you to take care of unsupervised learning problems with AutoEncoders. This training has been visited by nearly 20,000 students and has exceptional reviews and ratings.

Applied AI with Deep Learning

Applied AI with Deep Learning is the third course in Advanced Data Science with IBM Specialization. Data Scientist Romeo Kienzler imparts his experience in the field to offer essential insights into deep learning. He covers a few core subjects, including deep learning frameworks, applications, scaling and deployment.

Past the video lectures used to present the material, you’ll be needed to finish readings and tests. The readings supplement the guidance given in the exercises and tests help recognize areas where you may require more work.

Register for free, and you should expect to go through 18 hours working through the course material.

Deep Learning – Google via Udacity

In this course, you’ll build up a clear understanding of profound learning, and build intelligent systems that learn from complex and additionally huge datasets. You will figure out how to tackle new classes of issues that were once thought restrictively challenging, and come to better appreciate the complex nature of human insight as you take care of these equivalent issues easily utilizing deep learning techniques.

Deep Learning Nano Degree Program (Udacity)

People who need to study how to build and apply their own deep neural networks to different issues like image classification and generation, time-series prediction, and model deployment can take help from this nano degree program. This program is exceptionally made for students who are keen on making a profession in machine learning, artificial intelligence, or deep learning. Taking a crack at this program will acquaint you with Deep Learning algorithms, neural networks, and deploying a sentiment analysis model. In the wake of completing the program with given tasks and projects, you will get a certificate of completion that can be shared with your resume and employers.

Natural Language Processing with Deep Learning – Stanford University

The course gives a careful prologue to forefront research in deep learning applied to NLP. On the model side we will cover representations, window-based neural networks, recurrent neural networks, long-short-term-memory models, recursive neural networks, convolutional neural networks as well as some ongoing models including a memory part. Through video lectures and programming tasks students will gain proficiency with the essential designing stunts for making networks work on practical problems

The post 10 BEST ONLINE AND FREE DEEP LEARNING COURSES appeared first on Artificial Intelligence.

In recent months, educators have had to change their lesson plans and I’ve been amazed by the new and fun tactics that have emerged to engage students. Like many others, I struggled at first with the transition to an online setting. I teach robotics to middle schoolers; my classroom is very hands-on. When the school closures went into effect, I had a new class of 30 middle-school students that I had to teach virtually.

I’ve had the additional challenge of maintaining high attendance. Robotics is an elective course and most students are focused on their core requirements during this time. It has been difficult to teach a new group of students about robotics. However, it’s forced me to create engaging lesson topics and demonstrations to help keep students interested and tuned into my class each week.

Just before schools closed, I received a LEGO Education SPIKE Prime Set, a STEAM learning solution — designed for middle schoolers — that combines the signature bricks with coding. The platform emphasizes problem-solving and critical thinking by incorporating themes that are relevant to students’ daily lives. I was disappointed that my students couldn’t use the program right away. But, after some trial and error, I have been able to incorporate SPIKE Prime into my virtual robotics lessons. Here are a few of the tips and tricks I’m using with my students. 

Show Your Robot Running Its Code

I have a robotics set at home but my students do not. They can, however, download the free SPIKE app to their home devices and use the drag-and-drop coding language based on Scratch to create their own code and solve problems. 

When we meet virtually, I show them what I built. I share my screen so they can see the code I’ve created to make my SPIKE Prime move in different ways. Then I ask my students to write their own code, using the app, and they each share it with me. I run each student’s code so he or she can see how the code affects the way the robot reacts.

Rethink Boundaries

We teachers watch our students hold back because they are nervous about making a mistake. Take advantage of students not having the pressure of being in front of classmates to challenge them further. Encourage them to experiment with more difficult coding sequences. Use lesson plans designed for trial-and-error learning — as opposed to focusing on getting the right answer on the first try. Let them collaborate in teams. I watched my students work together, learn from their mistakes and solve impressive sequences — all while distance learning. 

Another idea: Try pushing your students to finish their programming at a faster pace than they would in the classroom. The added time constraint helps motivate them to problem solve faster and feel an even greater sense of achievement. 

Lead By Example

Our students are resilient learners, open to trying new things. Continue to take advantage of video conferencing, rethink your teaching boundaries and discover new ways to engage your students. Don’t be afraid to experiment. We’re asking our students to lean into new ways of learning, so we too must embrace this mindset. 

Also, give positive and timely feedback. Students are used to receiving immediate feedback on their coding in the classroom, so it is important to follow this practice with online instruction. Not only can students more quickly address their coding sequences, but they will continue building their confidence and feel a sense of pride in what they learn. 

Ian Chow-Miller is the robotics teacher at Frontier Middle School in Graham, Washington and a LEGO Education Master Educator. He uses LEGO Education Spike Prime for virtual robotics learning. 

The post Tips and tricks for teaching virtual robotics appeared first on Artificial Intelligence.

Richard Pilling considers the ethical responsibilities of delivering Machine Learning solutions and suggests that the immense possibilities opened up by ML should always be tempered with an understanding of potential consequences.

I was lucky to grow up in the 80s as the youngest of three children – a happy time of riding around on my Raleigh Grifter, watching Knight Rider, and playing on my Commodore 64. My

mum had a totemic and often repeated phrase of “just because you can, doesn’t mean you should” – which has always stuck with me; it was part of my mum teaching me right from wrong. It’s no surprise she went on to have a career as a social worker; helping disadvantaged children find safety, peace of mind, and good families. She instilled in them the same strong ethics as she taught me. At that time my dad was the head of Quality Assurance for a multinational, had helped invent Astroturf, and went on to write what would become ISO 9001. In essence, my upbringing was heavily influenced by a strong sense of ethics and a deep understanding of the value of innovation, and quality.

The Machine Learning revolution

We’re on the cusp of a worldwide revolution in Machine Learning – a wonderful set of tools and technologies, which have huge potential to either make the world a better place or further divide it. There’s always an ethical side to any new and potentially market-changing technology. However, unlike previous industrial revolutions, machine learning is focused on the ‘why’ of things, rather than the ‘how’ – or to phrase it another way: for the first time we’re inventing a better thinker, rather than a better ‘do-er’.

Companies have the ability to make systems that will fundamentally transform billions of lives,  all at the click of a button. Consider areas such as lack of transparency in decision making, unconscious bias, the law of unintended consequences – all to rain down upon millions and millions of unsuspecting people – the impact on society is, and will increasingly be huge.

Decisions framed as unbiased and data-based are still decisions based on what the machines have been taught from humans. We are responsible for determining what defines a “good” outcome, although it may not be a universally positive result. It’s more likely that these decisions are only useful in certain contexts and not others.

The machine, or its algorithms, does not have a sense of right or wrong as naturally have. We have a moral sense, that machines cannot learn (at least for the foreseeable future), as it’s making all decisions on data and acts as it’s told to do. It’s crucial to understand how these systems make decisions, to know why they’re being made.

There are some types of machine learning or certain algorithm classes that are more transparent than others. Some people are specifically making algorithms that are designed to be transparent so you can follow and expand on the thought process. A system that recommends, not makes, decisions and is able to explain them will be of great help across many industries.

I want to make sure that we’re not being too negative about machine learning. It is a really useful set of tools and technologies. It’s just, at the end of the day the fool with a tool is still a fool, just quicker.

Machine learning can build a bright future for us – but I’d like any singularity which may happen to be an inclusive benevolent one, rather than a nightmarish world of an all-knowing BigBrother. If you’re running at the pace of innovation, and it’s making you run as fast as you can, you need to stop and check that you do the right thing.

The time to think about this is now, before the cat is fully out of the bag.

Tech companies need to deeply consider the effects of their work – their role is to advise and help companies on the use of innovative technologies and make sure they don’t fall down a rabbit hole or ride too far on the hype-train. It’s a moral imperative to look at the ethical side of any technology, as well as its potential business value. The impact of machine learning is a topic that garners much attention, and this conversation mirrors the tenets of my upbringing: innovation, quality, ethics.

I have the good fortune to, at times, mentor bright-eyed newcomers to the world of big data and ML. I advise them to envisage the future ramifications of their work, and I often think to myself, just because you can, doesn’t mean you should!

Some things are best left to human beings…

I’d like my children to have as free and as happy a childhood as I did, discovering things rather than having an algorithm recommend them – as that can lead to an echo chamber. In this case, we should remember that some things are best left to humans. When growing up, my sisters gave me a love of music – especially 70’s disco and 80’s new-romantics. While I’m sure a streaming service algorithm could have led me that way eventually – I’m certain that the music wouldn’t mean anywhere near as much to me!

There are clearly thousands of use cases where ML can help optimise our experiences. However, let’s not forget the need for a ‘human’ element to enrich those experiences.

The post The ethics of Machine Learning: Just because we ‘can’ doesn’t mean we ‘should’ appeared first on Artificial Intelligence.

Kennesaw State Professor of computer science Dr. Dan Lo and his team of students created a program last semester to data mine Chinese social media sites in partnership with the U.S. Embassy in Beijing, China.

Lo said the program retrieves and deciphers posts on popular Chinese social media outlets like Weibo and WeChat. Lo’s team of student researchers — four undergraduates and two graduates — conducted extensive data mining on China’s Weibo platform and in turn, gained valuable real-world experience under his tutelage.

Weibo, meaning “micro blog” in Chinese, is an open social platform with over 445 million monthly active users. It is similar to both Facebook and Twitter, and likewise is an epicenter of Chinese news.

Lo said he is passionate about the project as it embodies elements of social networking, big data, machine learning and data science. Additionally, it required fluency in both Chinese and Python, a coding language. The team’s biggest challenge was processing Chinese articles correctly because of the complexity of the Chinese language.

“Chinese language is highly context-sensitive. Consecutive Chinese letters can be combined and interpreted in multiple ways.” Lo said. “For instance, our data mining programs needed to determine if ABC was meant to be read as A, B, C, AB, BC or ABC in the mind of the writer. The meaning in each instance varied vastly.”

Handling word segmentation, numbers, acronyms, synonyms and newly developed words in Chinese slang posed additional frustrations. Linguistic challenges and the sheer volume of the big data analyzed required painstaking efforts to codify the inputs.

“Social media mining in English has been performed for many years in Twitter, Facebook, Instagram and other networks,” Lo said. “While it is theoretically possible to do the same in Chinese by applying most of the English techniques, it is not that simple.”

Information sharing on social media is a valuable tool in forming public opinion. The results from the project enabled Lo’s team to show the information shared among Chinese users and the key statistics of that data.

“Dr. Lo is an excellent mentor because he allows his students to have a role in all stages of the research process,” graduate research assistant Charles Gardner said. “By working so closely with his students, Lo creates strong researchers as well as a great finished project.”

Gardner has been working as a graduate research assistant for Lo for over a year now.

“In English, we do not have word segmentation,” Gardner said. “However, in this project, we look at Chinese words within references and it ends up being an interesting system.”

Lo has already begun work on his next exciting project identifying fake news and dealing with misinformation. This new project has been commissioned by the U.S. Embassy in Poland.

The program was awarded to KSU by the The Diplomacy Lab, an alliance between the U.S. Department of State and U.S. colleges and universities, according to KSU News. Under the program, partner U.S. universities are invited to submit proposals for State Department projects in various humanitarian areas.

The post Computer science team creates coding program to interpret Chinese social media texts appeared first on Artificial Intelligence.

Aspirants and professional data science today swear by the popular and trending buzzwords. They use their energy in taking up numerous projects and eventually get exhausted. Rather than padding their resumes, aspiring data scientists should work on specific projects that have not been done yet. However, since most of the MOOCs have projects like house pricing prediction or flagging frauds, developers fail to differentiate their capabilities. Besides, deploying machine learning and deep learning techniques are not enough to obtain job offers, one should have the business domain knowledge along with data science techniques for assisting firms in making informed decisions.

To help students adopt best practices, Analytics India Magazine interviews prominent data scientists every week and brings out their story to help aspirants understand the right approach. For this week, we got in touch with Bastin Robin, Chief Data Scientist at CleverInsight, for our weekly column My Journey In Data Science.

Robin’s Interest In Computer Science Began With Designing

While in school, Robin was in love with computer science. However, it was more inclined towards designing than programming. He created a portfolio pertaining to design, which helped him in getting various freelance jobs. Eventually, he turned his passion into a business and started a firm called W3Graphix in 2009 – a design consulting company. Although Robin was earning before even joining the college, he enrolled in an engineering college to get a certificate. 

Love And Hate For Programming

Robin pursued computer science engineering, but he wasn’t interested in programming. However, his Head of Department, who had a PhD in data mining, used to push him to learn to code. The HOD used to say that Robin could not become an engineer if he does not learn to code. But, Robin did not agree and believed not everyone is the same; he was confident of having a great career without the programming skills. Irrespective of Robin’s interests, the HOD kept pushing him and explained the importance of programming for being competitive in the tech world.

According to Robin, he was doing well in college and was selected as a Microsoft Student Partner. However, one morning, he decided to heed and for once do what his HOD expects from him. “The cold war between me and HOD lasted for too long. And since he was insisting, I thought about giving it a try, explains Robin. “And it changed everything for me,” he added. 

Unlike others, Robin didn’t start with popular languages like C, C++, and Java. He went to the library and picked up the book introduction to programming. The book had lessons that were explained in Python programming. Robin immediately fell in love with the book, and for the next two to three months, he read it like a bible. “That’s the only book I carried to the college and people thought that I had gone mad,” says Robin. “C and C++ are very sensitive to syntax, whereas Python is more of an expressive language. Therefore, anyone who learns Python enjoys it from the very beginning.”

First Data Science Job

While being in graduation, Robin was asked to teach M.tech students due to his Python programming skills by one of the assistant associate professors. Within no time, he was able to convince the class filled with M.tech students the essence of programming, and this made him believe that coding was his cup of tea.

During his final year, one of the students from the M.tech informed Robin about the opening at Gramener. Immediately, Robin applied through its career page and was asked to solve three data science problems. On submitting the solutions, he was called for a face-to-face interview with the CEO and VP of Gramener in Hyderabad. Impressed by his skills, Robin was offered the associate data science job by the management.

Job Experience

While working at Gramener, Robin worked on various use cases to help the firm achieve its business objectives. One of the projects that really made the difference was optimising the logistics with data science practices. “Data science has four pillars: past, present, future, and the action. It is not about the tools rather, data science is to make informed decisions that require business knowledge. Consequently, the fourth pillar is of utmost importance,” believes Robin. 

He further went on to say people try to focus on machine learning and deep learning techniques, but data science is about data, not fancy ML and DL. Positive ROI is what matters the most, which can only be achieved by obtaining business domain knowledge.

After being with Gramener for a few months, Robin was motivated enough to start a data science firm that would offer SaaS-based data science platform, where one can drag and drop to visualise. Therefore, he laid down the cornerstone of Hash Research, which immediately got traction from various businesses. Further, he started working on multiple use cases and showcased his capability using platforms like LinkedIn and blogging sites.

Passionate to further enhance the product of Hash Research, Robin along with Kothandaraman Sridharan, founder co-founder of Mphasis, established CleverInsight that acquired Hash Research. “We built a platform called Neuron AI, which was basically an advanced version of the product of Hash Research, litmus,” describes Robin. “Neuron AI is an ecosystem where one can build many use cases on top of it.”

Advice To Data Scientists

Aspirants and professionals of data science mostly focus on projects that are already available on the internet. For instance, people try to refine their resume with projects such as fraud detection model, image classification model, and more. However, Robin says that there is nothing new in it; such projects are all over the place. Instead, he suggests developers should create dummy datasets that can resonate with business problems and then try to ask various questions and solve them accordingly. Going one step further will assist them in demonstrating your capabilities and quickly get their desired jobs. “Interviewers look at how the applicant started from zero to end. The process of doing specific cases will impress any recruiter, thereby increasing the possibility of receiving a job offer,” concludes Robin.

The post HOW THIS CHIEF DATA SCIENTIST OVERCAME HIS DISINTEREST IN CODING appeared first on Artificial Intelligence.

After seeing great success for their online platform, EdTech startup WhiteHat Jr. today announced its plans to bring their artificial intelligence and robotics coding curriculum to schools across the country. Coding and artificial intelligence has gained immense interest amongst schools in recent times, not just for future-proofing the next generation, but also as a result of government policy.

Earlier this year, Central Board of Secondary Education (CBSE) decided to include artificial intelligence in their syllabus for students from class 8 to 10 as an optional subject and coding is quickly spreading as a viral phenomenon amongst kids across the country.

WhiteHat Jr. will collaborate with schools in three different models. In the first model, the company will license their curriculum to schools where they will train teachers on the curriculum and on how to best deliver it to students. In the second model, the EdTech startup will supplement the school’s existing computer science class and teach students in the schools’ computer labs via 1:1 live, online classes. In the third model, WhiteHat Jr. will help schools form post-school coding clubs and conduct coding classes to complement their existing computer science curriculum.

Mrs. Kajal Chhatija, Principal, Global Talent International School, said: “Learning coding and AI from a young age will soon become a culture. We are in the age of collaboration and integration in which they are essential skills to make our students future-ready and should be taught right from an early age. The concepts must be introduced in the foundational years like recognition of alphabets, numbers and phonics. As educators, we face difficulty in translating a highly technical field like coding into a structured, sequential curriculum that can be learned by the children across all ages. WhiteHat Jr’s specially developed curriculum covers technologies like AI and Machine Learning in an interactive and engaging way and the best part are the 1:1 online classes. We’re excited to collaborate with them to make our students at GTIS future-ready for coding and AI.”

About the initiative, Karan Bajaj, founder and CEO, WhiteHat Jr. said, “While kids today learn the basics of computing in schools, there is an immediate need for a comprehensive and well researched approach to teaching them coding. We’ve developed the world’s first coding curriculum for kids which includes cutting-edge fields such as AI, robotics, machine learning and space tech. Our curriculum has been created by MIT/IIT computer scientists and we have seen proven results over the past year. We believe that there are great synergies for schools to collaborate with us and we are witnessing an overwhelming demand from schools across the country. We’re currently in discussions with over 150 schools to roll this program out.”

Over the past year, young kids have created some incredible apps on WhiteHat Jr.’s platform. 7-year-old Hirranyaa Rajani has created a sign language app for the hearing-impaired children while 8-year-old Shrey Shah has created a 24×7 School Communication channel like Slack where parents, kids and teachers can be connected at any point in time and post real-time questions.

WhiteHat Jr has also rolled out a program where top 1% of kids on the platform will have a chance to get an all-expense paid trip along with one of their parents to Silicon Valley to be mentored by top entrepreneurs and venture capitalists.

The post WhiteHat Jr. brings artificial intelligence based coding to Indian schools appeared first on Artificial Intelligence.