IIIT Bangalore is offering a free cryptography course on NPTEL for beginners who want to learn about various techniques to secure data. The course does not require any prerequisites, but it is recommended to have an understanding of discrete mathematics, algorithms, or the theory of computation.
The cryptography course by IIIT Bangalore is devised to make you ready for any IT industry as it focuses on the foundation of cryptography. In this digital age, when you deal with a colossal amount of data either in personal or professional life, a knowledge of modern cryptography can provide you with an edge over others.
Organizations not only need someone who processes data but also has an understanding of securing data. Data protection has become crucial for organizations with the new privacy law in place. Failing to fortify data while leveraging users’ data to build data-driven products can lead to steep financial losses.
Since data is everywhere, the cryptography course by IIIT Bangalore is a must to build your foundation on cryptography. Some of the key topics covered during the 12-week-long course are — computational security, authenticated encryption, number theory, and more.
The lessons will be taught by Dr. Ashish Choudhury, associate professor at IIT Bangalore, which would be based on books like Introduction to Modern Cryptography by Jonathan Katz and Yehuda Lindell and Cryptography Theory and Practice by Douglas Stinson.
The course will start on 18 January 2021, but you can register till 25 January 2021. After completing the course in the second week of April, you can also opt for certification by taking an exam after paying ₹1000. However, the exam for certification is optional. But if you opt for certification, you will only get a digital certificate instead of hard copies.
You can enroll in the Foundation of Cryptography by IIIT Bangalore course here.
Cognizant acquires Inawisdom, a UK-based AI, ML, and data analytics consultancy firms, on Monday in an undisclosed financial transaction. With this acquisition, Cognizant closes ninth acquisition in 2020, shelling out over $1.1 billion this year for mergers and acquisitions.
Highly focused on AWS technologies, Inawisdom has gained clients in Europe and the Middle East to assist organizations in adopting data-driven techniques effortlessly. Inawisdom has also developed Rapid Analytics and Machine Learning Platform (RAMP) using AWS technologies to streamline its services for organizations with continually evolving and reusable code repositories for making accelerated data-driven decisions.
Talking about Cognizant’s acquisition of Inawisdom, Malcolm Frank, President, Digital Business of Cognizant, noted business succeed and fail by the speed and quality of their decision, and the best business decision is informed by data and AI. “We are pleased to welcome Inawisdom’s skilled team to Cognizant and further accelerate our innovation on data modernization and intelligent decision-making.
Started in 2016, Inaswisdom has been named by AWS as APN Machine Learning Partner of the Year 2020 and APN Differentiation Partner of the Year 2019 in Europe. Inawisdom has expertise in optimizing the supply chain, customer service, operational efficiency of organizations to bring profitability within weeks.
“As a committed and proven expert in AI and machine learning, we are excited to join Cognizant and build on Inawisdom’s unique combination of accelerators and skills,” said Neil Miles, CEO, Inawisdom. “Our combined strength will further support customers in embedding data-driven decision-making into their organization, increasing their speed to business value and long-term market differentiation.
Inawisdom will join Contino, a Digital Business group of Cognizant in London. Contino was acquired in 2019 that assists organizations with DevOps methodologies and advanced data platforms. With Inawisdom’s acquisition, Cognizant will further enhance it’s AI and ML capabilities to serve its customers. Cognizant is already recognized as Leader in Gartner’s 2020 Magic Quadrant for Public Cloud Infrastructure Professional and Managed Services, Worldwide.
AI became a co-pilot on a U-2 spy plane to control crucial sensors during a fleet at Beale Air Force Base, California. The AI system was named ARTUµ, which was based on µZero — an open-source algorithm developed by DeepMind to outperform humans in chess, Go, and video games. AI in the US Air Force marked the beginning of an era of advanced military operations, where AI will play a significant role in defense systems.
Although the AI was assigned a specific role — search enemy launchers, the human pilot was the final decision-maker. The US Air Force trained the µZero to operate radar effectively and identify enemies.
Former chairman of the Defence Innovation Board, Eric Schmidt, said that this is the first time, to his knowledge, AI is integrated into any military. Trained over millions of simulations, the ARTUµ was ready in just over a month.
According to the pilot, who said to the media, the task of AI’s role was narrow, but for the functions the AI was presented with, it performed well. In a two and half hour test, the AI controlled the radar system but was cut-off from other subsystems.
The US has been extensively leveraging the latest technologies in defense to revolutionize the way they conduct military operations. For this, they join hands with tech giants like Microsoft and Google for cloud and cybersecurity. In this particular test, the AI system was deployed on an open-source platform, Kubernetes, for managing containerized workloads.
With AI in the US Air Force, in the future, the US has plans to surpass science fiction in terms of the capabilities of machine intelligence. It may seem like a distant dream, but AI in the US Air Force is a breakthrough that will push other governments across the world to pursue similar goals, thereby expediting the speed of the development of AI in defense.
OpenAI releases robogym, a framework that provides simulated environments to train robots and enhance their capabilities. robogym uses other toolkits like OpenAI gym and MuJoCo physics simulator. While OpenAI gym offers an end-to-end suite of reinforcement learning tasks, Multi-Joint dynamics with Contact (MuJoCo) is a physics engine for robotics that facilitate research and development in a simulated environment.
Using robogym, you can not only visualize and interact with environments but also change the parameters of environments for diverse virtual settings. You can even teleoperate to manually manage a robot’s interaction using a keyboard, thereby giving varied capabilities to train robots to ensure it delivers superior performance.
As per Statista, global robotics market revenue will hit $100 billion, and by 2025 the market size will reach $210 billion. Machine learning, a major driver of the adoption of robots, is playing a significant role in the rapid adoption of robotics. Therefore, frameworks like OpenAI robogym will open up a wide range of opportunities for learners to quickly develop robots that can assist organizations as well as the general public in automating tasks.
In 2019, OpenAI had made a breakthrough in robotics with its Automatic Domain Randomization (ADR) technique that allowed its robot — Dactyl — to train in different environments to solve Rubik’s cube. The simulator incrementally increased the complexity of the environment with randomization for the robot to train and enhance the dexterity of the robot.
It was one of the major developments in artificial intelligence as the technology shed light on machine learning’s general intelligence since the robot was able to perform in environments in which it was never trained for.
With OpenAI robogym, you can leverage the Dactyl environment that has a robotic arm with 20 actuated degrees of freedom to perform manipulation tasks. There are further sub-categories within this environment that can allow you to train robust robots with machine learning capabilities.
MIT releases a free machine learning course that focuses on principles, algorithms, and applications of machine learning. The 13-week long course is designed to teach supervised and reinforcement learning.
According to the course description, the objective of the course is to understand the formulation of well-specified machine learning problems and learn how to perform supervised and reinforcement learning with images and temporal sequences.
Devised by MIT in 2020, this course is a must for enthusiasts who want to become proficient in various machine learning techniques. Along with video lessons, the course includes exercises, labs, and homework problems. This enables learners to get hands-on while learning new machine learning techniques.
However, there are a few prerequisites like Python, calculus and linear algebra for taking the course. But, you can start the course even if you have a knowledge of Python and learn calculus and linear algebra as you progress through the course.
Some of the key topics the course covers include feature representations, margin maximization, regression, reinforcement learning, and various neural networks.
Register for the MIT free machine learning course here.
Microsoft AI Classroom Series was started in September to make students ready with emerging technologies like AI and Cloud Computing. This session of the Microsoft AI Classroom Series will cover data science lifecycle and cognitive services, building machine learning models on Azure, and intelligent conversational AI. Students will also get exclusive Microsoft Official Course (MOC) material for the AI-900 course during the session.
The video session will be delivered by speakers from industry experts from Microsoft India, NASSCOM FutureSkills, IIT Madras, Wipro, and more. This program, however, is only for students enrolled in Indian universities and are residents of India.
After completing the Microsoft AI Classroom Series session, learners will receive an email from taking an online assessment, where they will have to answer 30 multiple-choice questions. On getting a score of 60 percent or more, they will get a “Microsoft AI workshop” certificate of participation. However, aspirants will have a total of 3 attempts to pass and receive the certification from Microsoft and NASSCOM FutureSkills.
The first session starts on 14 December, which also includes a Live Q&A during the event. Although seats are limited per session, you will have an opportunity to choose from any session starting from 14 December to 19 December. Irrespective of which session you attend, the assessment test will be active only from 19 to 30 December. Make sure you clear the examination within three attempts before 30 December to get the certificate.
There are a few prerequisites to attend this session of the Microsoft AI Classroom Series to ensure you make the most out of the upcoming sessions. You can access suggested prerequisite materials of Get started with AI fundamentals, Azure Cognitive Services, Introduction to Azure Machine Learning Services, How to create bots with Azure Bot Service.
There are other requirements like VSCode Jupyter Notebooks setup, GitHub account, and more to simplify the session’s learning process.
FutureSkills Prime is offering a big data foundation course with certification for a limited time. The program is devised by Digital Vidya, which includes videos and projects, and more. According to the course description, it would take 55 hours to complete and get certified by Digital Vidya and NASSCOM. However, you will have only one attempt to complete the course, which is free till 17 May 2021.
Big Data course has three modules — introduction to big data analytics, big data fundamentals and platforms, big data processing, management, and analytics. The course includes video lessons on prominent big data platforms MongoDB, Spark, Map Reduce, and Hadoop. While you might not get to learn all the in-depth techniques of the tools, you can get an overview of big data platforms’ capabilities and implementation.
The course also imparts knowledge about data pipelines, which is an essential part of data management in organizations to streamline the data science workflow, thereby making it a complete foundational course for big data analytics. The course also allows you to download materials that can be handy while working with big data tools for quickly setting up the environment for projects.
In an attempt to democratize digital skills among people, FutureSkills Prime was launched in a joint partnership among the Government of India, Ministry of Electronics and Information Technology, and National Association of Software and Services Companies (NASSCOM). The platform will include courses on emerging technologies like Artificial Intelligence, Augmented and Virtual Reality, Blockchain, Cloud Computing, Cybersecurity, Robotics Process Automation, Web and Mobile development, and more.
Although it is still in the beta phase, learners can leverage the FutureSkills Prime platform to learn from courses available for free created by industry experts. The platform will further include more courses in the future to ensure learners have access to learn cutting-edge technologies.
Register for the FutureSkills Prime Big Data Course for free.
PhonePe’s data science team acts as one of the foundational pillars of its payments service to millions of people across India. Founded in 2015, the company became the most widely used payment service, amassing 40% of the total UPI payments with 925 million transactions overall in October 2020. Being trusted by 250 million users, PhonePe extensively leverages machine learning to ensure customer trust in a highly regulated industry. A strong Data Science culture is a key pillar for the rising popularity and leadership of PhonePe in this highly competitive space.
To peek into the data science culture of the company, Analytics Drift got in touch with Kedar Swadi, head of data sciences at PhonePe. Kedar shared interesting insights into the data science team of the Walmart-owned payments company, as well as shared his opinions on best practices for aspirants to flourish in their careers.
How Is Machine Learning Leveraged At PhonePe?
Machine learning not only helps PhonePe users and partner merchants enhance customer satisfaction but also is leveraged within the organization to optimize business processes for increasing revenue and reducing costs. “Data science is at the core of a lot of decisions that we make at PhonePe; we utilize patterns in users’ payment history to remind them about the right payment at the right time,” says Kedar. It may be a payment to another user or a bill that one should not miss or recharge to keep the continuity of services. Besides, with superior machine learning techniques, PhonePe ensures that it identifies potential fraudulent users as early as possible to maintain a healthy payments ecosystem.
PhonePe’s Data Science Culture
“One of the many great things about data-driven PhonePe is its data science culture. We thrive on taking up hard problems while limiting the risks and experimenting to arriveat better solutions,” explains Kedar. The decision-makers back the data science efforts to enable the team to blaze a trail in various payment aspects. Data scientists at PhonePe are provided with the necessary time to explain the problems, gather information, and extract value from multiple data. With this, PhonePe allows innovation and accepts failures as a part of data science initiatives to keep the team motivated during setbacks.
While following the right set of principles to drive the team is one aspect of thriving in the competitive market, having the right professionals who fit in the culture is equally important. And since it takes years to understand the basics, tools, and techniques for a data science job, PhonePe relies on professionals who have two to three years of experience in the field. However, Kedar believes there are always exceptions, even for someone who wants to change careers but may have to start at the entry-level and build the required skills.
And when asked about the critical skills he seeks in data scientists while hiring, Kedar said that a strong background in algorithms, basic statistics, optimization, and programming skills is a prerequisite. Although some experience in the application of multiple machine learning algorithms helps, he believes new algorithms can always be learned on the job if one has obtained foundational skills. And since data science is also a communication-heavy discipline, Kedar stressed the importance of effectively communicating, whether it is to understand the problem or explain the results. Apart from the aforementioned skills, he evaluates applicants for the cultural fit-aspirants who can work in hierarchy-less organizations like PhonePe.
But how does PhonePe hire the desired data science professionals? Hiring data scientists is a massive challenge for organizations due to the talent gap in the market. As a workaround, PhonePe looks out for good people and then provides them with the support and opportunities to grow and get better. “A lot of emphases is laid on teamwork and supplementing each other’s skills. We look for people who show other valuable traits like curiosity, perseverance, self-motivation, and desire to excel,” says Kedar.
Do Data Scientists With Ph.D. Perform Well Over The Self-Learned?
According to Kedar, a Ph.D. implies a solid five or more years spent understanding a topic and the theory behind the techniques. This helps learners assimilate the strengths and weaknesses of a wide range of machine learning methodologies, enhance the ability to formulate and solve problems independently, and train to deal with failures. On the other hand, self-learning with MOOCs focuses on specific skills in a reasonably short time and in a fast-paced environment. Therefore, a Ph.D. has an advantage, but a few years of on-the-job experience by a self-learner usually reduces the gap.
Advice To Aspiring Data Scientists
Data science is about handling data, drawing insights from it, and communicating in a meaningful and actionable way with the various functions of an organization. To carry out all of these, one needs to have technical competence, domain expertise, and, most importantly, the right attitude.
“When it comes to technical competency, you need to have a strong foundation in algorithms, mathematics, and statistics. Learning new techniques when needed will become easy when you have acquired solid fundamentals. You should also be good at programming, know how to handle large amounts of data efficiently, and create scalable pipelines to work with ever-increasing amounts of data,” mentions Kedar.
“But domain expertise is acquired through experience. For instance, if you do not have sufficient knowledge about radiology, you will struggle to understand the data, problems, and other nuances of the field. Mastering even the sub-domains like banking, finance, insurance, investments and trading under the BFSI sector will take years. Consequently, steadily improving the data science skills in conjunction with domain expertise will be the key to a successful career.”
“Finally, as a data scientist, one needs to have the right attitude to believe in the process and not just implement glamorous machine learning techniques. 80% of data science is manual work of looking, cleaning, and processing data. This requires humility to work on non-glamorous aspects of data science. The tenacity to sift through a massive amount of data, the ability to deal with failures, and the strength to learn and get better are equally essential for data scientists,” concludes Kedar.
Backed by Alibaba, AutoX deploys 25 self-driving cars without safety drivers in Shenzhen, China. However, the service is not available for the general public just yet. In an interview, Xiao, founder of AutoX, said that it could take another two to three years for approval from regulatory authorities to offer fully self-driving cars to the public.
AutoX deploys self-driving cars
Founded in 2016, the company has delivered exceptional results quickly to impress regulators. On June 19, 2019, the company became the second in the world to operate robotaxi after obtaining a permit from California Public Utilities Commission. And in July 2020, the company tested its driverless car in California without a safety driver.
Robotaxi, a self-driving ride-hailing service with safety drivers, has gained prominence in the US and China, where AutoX has been at the forefront. The company’s success in mere four years can also be attributed to the association with its partners like NVIDIA for DRIVE platform and FIAT Chrysler for rolling out fleets in Asia.
In addition, AutoX has a global presence for its technology and market with research and development in Silicon Valley and Beijing, and an operational center in Wuhan and Shanghai. To further ramp up the operation, the company has plans to deploy self-driving cars in three more cities.
Over the years, the race to become a leader in the self-driving cars market has become apparent as more than 60+ companies are testing autonomous vehicles. Although it started late, AutoX is making huge inroads in the industry and giving early starters like Waymo, Cruise, Zoox, and Tesla, a run for their money.
2020 has been the year where self-driving cars promise is materializing as many stakeholders are embracing contactless delivery of food and travel services. After a lot of criticism from experts about autonomous technology, the industry is making people believe that level 5 autonomy is around the corners.
Salesforce, a CRM platform provider, announces the acquisition deal with Slack for $27.7 billion. If the deal doesn’t hit any regulatory roadblock, it will become the biggest ever acquisition by Salesforce. Earlier, in 2019, the company had acquired Tableau for $15.7 billion. Like Tableau, Slack will also be integrated with Salesforce Customer 360.
Since the launch of Slack in 2009, the company has been at the forefront of simplifying communication for developers as well as organizations. Over the years, it integrated tons of services to make it an all-in-one platform for effective communication and process workflows. But, since the launch of Microsoft Teams in 2017, Slack has faced the heat of Microsoft’s deep pocket. And during the pandemic, when employees started working from home, the demand for collaboration rose exponentially, and Slack failed to capture most of the market.
Even though Slack was uniquely positioned to capture the gamut of the market share, the company struggled to compete with Microsoft’s sales workforce, thereby losing its advantage in the market. Although Slack quickly integrated necessary services like video calling of different platforms, Teams increased its ambit quickly in the collaboration tool since it offers office suite to organizations. Teams made a lot of sense for organizations than Slack due to its deep integration with office products.
This is yet another example of the rising monopoly of blue-chip companies that force small companies to get acquired. Google, another tech giant that only realized the importance of collaboration tools, is actively revamping since the pandemic. With meet, chat, and rooms, Google is also tapping into the market for ease of collaboration. Slack could sense Microsoft’s increasing dominance and witness the change in strategy by Google, which could eventually impede its business.
While collaboration tools like Zoom saw a sharp increase in stock price during the pandemic, Slack’s stock was trading below $38 per share, which was the opening trading price when Slack went public on NYSE last June. Slack was struggling when the market for collaboration tools was hot during the early part of the year. In such circumstances, one of the best bets for a company is to get acquired.
And what better partner other than Salesforce would Slack have had agreed to make this acquisition deal? Salesforce has a deep penetration in organizations with a must-have CRM tool. With the integration of Slack with Salesforce, it has the potential to streamline the business process within organizations. Maybe, now, the competition for the market share for collaboration tools is even; Salesforce can fight shoulder to shoulder with Microsoft. At the same time, Google will now not have a straightforward path to penetrate the market. But, people would not complain even if Google comes into the ground zero with Microsoft Teams and Salesforce’s Slack vying for the top spot.
