The US Department of State has selected four distinguished scientists to serve as Science Envoys for 2024. They are Dr. Rumman Chowdhury, Dr. Stephanie “Steffi” Diem, Dr. Sian Proctor, and Dr. Dawn Wright.   Through the US Science Envoy Program, eminent American scientists and engineers leverage their expertise and networks to forge connections and identify opportunities for sustained international cooperation to advance solutions to shared challenges, champion innovation, and demonstrate America’s scientific leadership and technical ingenuity.   The scientists selected to participate in 2024 make up the first all-female cohort in the history of the US Science Envoy Program, said the US Department of State. The US Science Envoy program was established by the Secretary of State in 2010.   Read: Irish Minister Simon Coveney pays homage to Father of the Nation at Dhanmondi-32 Like their 30 predecessors, the 2024 Cohort will travel as private US citizens to engage internationally with civil society as well as government interlocutors.   Science Envoys help inform the Department of State, other US government agencies, and the scientific community about opportunities for science and technology cooperation.   The State Department selected the 2024 cohort to take advantage of their expertise in key issues facing the world today: Artificial Intelligence, Fusion Energy, Civil Use of Space, and Ocean Sustainability. Dr. Rumman Chowdhury is a data scientist and social scientist. She is the CEO of Humane Intelligence, a technology nonprofit that builds a community of practice around evaluations of artificial intelligence (AI) models.   Dr. Chowdhury is also a Responsible AI Fellow at Harvard University’s Berkman Klein Center for Internet and Society.  Previously, Dr. Chowdhury served as Director of the Machine Learning Ethics, Transparency, and Accountability team at Twitter, as well as the Global Lead for Responsible AI at Accenture Applied Intelligence.  Read: UN envoy: Finding that some hostages were victims of sexual violence doesn’t justify Israeli attacks She has earned numerous awards and accolades, including Time Magazine’s 100 most Influential People in AI, BBC’s 100 Women, Worthy Magazine’s top 100, the Bay Area’s top 40 under 40, and Forbes’ labeled her one of Five Who are Shaping AI.   Dr. Chowdhury holds two undergraduate degrees from MIT, a M.S. in Quantitative Methods of the Social Sciences from Columbia University, and a Ph.D. in political science from the University of California, San Diego.

The rapid evolution of the technology industry has made tech skills increasingly vital in the current job market. As we approach 2024, staying abreast of the most in-demand tech skills is essential for anyone looking to secure a thriving career in this dynamic field. This comprehensive guide delves into the top tech skills that are poised to shape the industry in 2024, offering insights into how you can stay competitive and forward-thinking in your tech career. Most In-Demand Tech Skills to Advance Your Career in 2024 Cybersecurity In the realm of technology, cybersecurity remains a critical and rapidly growing field. As of 2023, there is a demand for almost a million cybersecurity professionals globally, but there are about 400,000 professionals across the world. The cybersecurity landscape is vast, presenting numerous opportunities in various sectors. Aspiring cybersecurity professionals should begin with foundational knowledge in network security and protocols, progressing to more complex topics such as virtual machines, remote access, intrusion detection systems, cybersecurity frameworks, and risk management strategies. Read more: Cyber Security Career Guide: How to Become a Cybersecurity Expert? Data Analytics Data Science and Analytics have become central to tech trends, with a considerable expansion in scope and application. Data analytics involves processing and interpreting large data sets to provide actionable insights for businesses and decision-makers. The US Bureau of Labor Statistics anticipates a 23% growth in demand for data analysts over the next decade. Key skills in this field include proficiency in tools like Microsoft Excel, Power BI, Python, and Tableau. Additionally, obtaining a degree or certification in data analytics significantly enhances one's career prospects. Cloud Computing Cloud computing has transformed the way we access and interact with technology, offering scalable computational resources over the Internet. The field has witnessed widespread integration across various industries such as tech, finance, automotive, and healthcare. Read more: Best Free Data Science, Machine Learning Courses Online For beginners, the journey into cloud computing starts with learning the basics of cloud infrastructure, management tools, deployment strategies, directory services, and architecture principles. Combining cloud computing knowledge with cybersecurity skills opens doors to specialized roles in cloud security. Robotic Process Automation (RPA) RPA is revolutionizing organizational workflows by automating repetitive and mundane tasks. This not only streamlines processes but also enhances efficiency and accuracy. Breaking into the RPA sector requires a solid technical background complemented by professional certifications and practical training. These qualifications pave the way for internships and permanent positions in the field.

The Entrepreneur Economist Club of Dhaka School of Economics organized a virtual seminar on the importance of big data and machine learning in entrepreneurship analysis. Speakers from different countries connected the seminar through online, while the students and faculties of entrepreneurship economics joined the program as hosts, held on Tuesday. The speakers emphasized increasing practice on machine learning and data analytics, to face the challenges of entrepreneurship in the new era. There is a possibility of major changes in the economic activities of the country. So any skills in machine learning and data analytics will put an employee ahead, they said. Read More;: Google's AI Chatbot Bard: All You Need to Know  Prof Parul Khanna, Vice Principal, IMT, Faridabad, India was the chief guest in the seminar while Economist and Coordinator of entrepreneurship economics Professor Dr. Muhammad Mahbub Ali chaired the session. Prof.Dr.Rinku Sharma Dixit, New Delhi School of Management, India presents a keynote paper on ‘using big data and artificial intelligence to accelerate entrepreneurial development Dr. Sudipta Bhattacharya, Dr. Dipika Kundal, Dr. Kunal Sheel, Dr. Pranjal Kumar Pukhan, Assistant Professors Rehena Parveen, and Dr. Sara Tasnim, among others, spoke at the function. Read More: ChatGPT maker releases tool to help teachers detect if AI wrote homework

Data science and machine learning have been the buzzword in the tech world for quite some time. The prospect of working with data, making clear and concise decisions, and a high payout career may seem lucrative to anyone. However, it’s not possible to become an expert in this field that easily. There are a lot of basics like statistics, programming, and analytics to cover before getting a hang of things. If all of these seem a bit too overwhelming, there are a few great foundation courses on data science and ML to get started from scratch. Check out which one best fits your needs. Why Should You Learn Data Science and ML? Let us ask you this, why shouldn’t you? Data science and ML holds the highest job prospect in the coming years. In fact, there are currently over 200,000 data science and ML-related jobs on LinkedIn alone. Industry leaders predict that the need for data scientists will increase by over 26% in the next 5 years. And the growth is expected to be exponential from thereon. While there are a lot of jobs at risk of becoming invalid due to automation and AI, the need for data science majors will forever be on the rise. And if the job security wasn’t enough to generate interest, the general median salary for a data science major in the USA is around 110,000 USD which roughly translates to 95,08,182 BDT per year. Did that grab your attention? Read along about how you can get started in your data science and ML journey. Read How to Be a Data Analyst from CSE or Non-CSE Backgrounds?  Top 9 Free Beginner’s Courses to Learn Data Science and ML  Data Science Specialization – Coursera This course is offered by Coursera in association with John Hopkins University. The free course is a mid-tier one designed for people who already have a grasp of the basics of statistics and R. The course will follow a detailed guide on using R to clean and sift data, manage projects and publish using Github, and data acquisition. It will also entail detailed regression analysis procedures using different regression models. The approximate course duration is about 11 months. Introduction to Machine Learning – Udacity Machine learning is almost as complicated as its name. It combines two significantly difficult disciplines – computer science and statistics to deliver a powerful predictive mechanism that makes up the base for modern data science. This intermediate-level course will introduce the students to the machine learning lens, data extraction process, and predictive algorithms. The approximate course duration is 10 weeks. Read Free Online Basic Programming Courses for Beginners Data Science Fundamentals – IBM Who better to learn data science from than the company that made the first computer? This beginner-level course is provided by IBM in association with Cognitive Class. The main aim of this course is to initiate the students with the very basics of data, its processes, life cycle, usage, and application. This course is part of a series of foundation courses that gradually progresses to intermediate and advanced levels. Students will also learn about different open-source data management tools. The approximate duration of the course is 10 weeks. Introduction to Data Science – Metis This course is a free introductory step to the data science boot camp offered by Metis. It is a small course that will be useful for beginners trying to get their head around data science. Students don't necessarily have to participate in the Bootcamp afterward, rather it’s a stepping stone to the world of data analytics. The 5-week-long course will see students learn about data cleaning, model creation, validation, and visualization. Read What is the Best Programming Language to Learn First? Machine Learning with Python – Coursera This Coursera course is supervised by IBM and is part of a series of machine learning levels. This is a beginner course that follows the integration of the commonly used programming language Python with ML. Students will learn about model evaluation, supervised learning, unsupervised learning, and different ML algorithms. The course will take approximately 22 hours to complete. Applied Data Science with Python Specialization – Coursera This applied data science course is fulfilled by the University of Michigan. This is an intermediate-level course with the main focus on the application end. Students wishing to get the basics first can check out the other 4 parts of this concurrent course. This specific course will focus on inferential statistical analysis and its implications, applied ML algorithms, and how to interpret results. The course will also focus on different data visualization techniques. The approximate course duration is 5 months. Read Game-based Programming: Best Coding Games for Children Data Quest Data Quest is an online platform that is all about data science and ML. But instead of the regular courses, the platform takes a more innovative approach to data science. Instead of having video lectures that guide the students first, the data quest starts with projects. While it may seem daunting at first, the interactive nature of the project and clear guidelines makes it easy for anyone to pick up the quirks. There are all sorts of resources available for free including paid plans. Data Science for Everyone – DataCamp This course is pretty much like its name. It’s a completely non-technical course focusing on the very basics of data science for absolute beginners. It starts by addressing what data science is and how it can be incorporated into modern jobs or how it benefits the big techs. It also gives an idea about how probability is related to computation and ML predictions. There aren’t any technicalities here so anyone can have a go-to to see whether data science is actually for them or not. Read How to Get a Job in Google from Bangladesh? Learn Data Science with R – Udemy The main basis of data science is made up of probability and machine learning. While ML mainly works with Python, data scientists need in-depth knowledge about R to get started with probability and regression model formation. This 10-part series from Udemy takes the students from the basics to the intermediate level of using R for data science. The course doesn’t connect the detailed dots with data management, but the students will learn much about sourcing and cleaning data for model applications. Final Words So far, we have shared 10 open source online courses for learning data science, data analytics and machine learning. Many people get attracted to data science just because of all the noise and prospects around it. But in reality, it's not everyone's cup of tea. But should that stop people from having a go at it? Absolutely not. Instead, these courses are a great starting point to see whether data science and ML match your passion and skill set and whether they can be a long-term career choice. Read Top 10 In-demand Tech Skills Freshers Should Learn in 2022