Digital technologies pretty much run the modern world. From our phones and computers to manufacturing, finance, and retail, so many aspects of life rely on machines crunching unimaginable quantities of data.

As a discipline at the core of this digital era, data science is still expanding its scope. Leading organizations in this sector never seem to get enough of new talent, and the demand for data science specialists is constantly rising.

Luckily, the same digital-first environment that depends on data science also gives ample opportunities for learning this essential trade. You can easily find a data science course online, and the same goes for certifications. Better yet, there are Masters programs you can take without leaving your home.

If the prospect of online data science courses sounds exciting, this article will recommend some of the best available programs.

Top Data Science Online Courses

There’s no shortage of options to learn data science online. The courses that made our list come from prestigious institutions and offer the most comprehensive approach to the subject.

When choosing the top courses, we followed straightforward criteria. We looked into institution reputation, hands-on experiences, lecture quality, and comprehensiveness. Here are the best online data science courses that excelled in these categories.

Metis – Data Science & Analytics Training

If you’re looking for an online course with live lectures, then Data Science & Analytics Training from Metis will be a great choice. The lecturers come from leading tech companies, giving lessons that cover the complete data science process.

While there are advanced bootcamps on offer, Metis provides a comprehensive beginner data science online course with certificate, which lasts for six weeks. The price for this course is $750 (roughly 695 euros at time of writing). This course offers an accredited certificate.

Dataquest – Introduction to Python Programming

Dataquest is somewhat unique as it represents a knowledge repository for standalone learning or as a supplementary resource. If you want to learn data science with this platform, the Introduction to Python Programming course is a quality choice.

The class is brief, informative, and suited for beginners. It consists of six lessons and a practical project, with an estimated 12 hours needed to complete the self-paced course. While the introductory course doesn’t offer certification, it will open up a learning path with Dataquest that does end up in winning an expert-reviewed credential.

A third of the learning resources is available for free. The full access to Dataquest courses will require a subscription to the service with a monthly or yearly model.

Harvard University – CS109 Data Science

Getting education from Harvard is about as elite as one can get. The CS109 Data Science course embodies all the benefits of learning from a prestigious institution like Harvard. The course teaches data science essentials, including Python programming, statistics, and machine learning. The complete material is accessible on dedicated GitHub pages. You can clone the repository to get access to the entire curriculum.

Since this is just the repository of resources, going through them won’t give you a certificate. However, it’s free and completely available online, making it an educational opportunity you shouldn’t miss. With the detailed knowledge of the basics under your belt, you’ll progress to more complex (and pricier) courses with ease.

Online Data Science Master’s Programs

You might think that getting a master’s diploma requires you to physically attend a college. And while that used to be the case only a few decades ago, you can enroll in a master’s program online. Better yet, you may do so at a reputable institution with a world-leading data science department.

We picked several top-tier online data science masters programs online. Our choice was based on similar criteria as for the courses:

  • How reputable is the institution?
  • Does the program offer practical knowledge?
  • Are the lectures comprehensive and quality-made?

With all that in mind, here are our top choices of online master’s programs in data science.

University of Aberdeen – Data Science MSc

The University of Aberdeen is one of the leading educational institutions in the UK. The Data Science MSc program is the university’s regular MSc data science online program that’s also completely available online. The curriculum includes vital skills concerning algorithms, data analysis, mathematical modeling, and more.

With full-time learning, the degree can be completed in one year. However, you can study at your own pace and take as much time as you need between individual courses. The limit for completion is six years, and enrolling in the program will cost £14,920.

Rome Business School – International Online Master in Data Science

The International Online Master in Data Science from the Rome Business School represents an excellent opportunity to learn, get in touch with industry-leading companies, and build a professional network. The school houses bootcamps across Europe and worldwide, which may increase your job market reach.

The participation fee for this program is €6,700. If paid after starting the course, applicants can split the cost into six installments, free of interest. Covering the fee in installments in advance will grant you a 5% discount. Paying in a lump sum comes with a 10% discount.

European Leadership University – Professional Master in Data Science & Leadership

The European Leadership University offers a comprehensive program that includes individual and group work, as well as interactive workshops. Completing the Professional Master in Data Science & Leadership program will earn you a master’s degree and two recognized certificates: in data science and leadership.

The program is priced at €5,000, with the option to pay the fee in five installments during the study period. Upfront payments come with a 10% discount. The program includes classes on machine learning, statistics, data collection and handling, Python programming, and more. This master’s course lasts for 19 months.

Key Skills to Learn in Data Science

Data science consists of numerous fields, some of which are more theoretical while other lean heavily towards practical applications. The later data science aspects include essential skills that you can use in the market:

  • Programming languages
  • Data visualization and reporting
  • Machine learning and AI
  • Big data
  • Statistics

In programming, languages like Python, R, and SQL are used to create program environments and write specific commands. As a data science skill, the study of programming languages explores the limitations and possibilities of existing and new languages.

Data visualization deals with representing complex datasets in a more comprehensive way. It’s related to reporting and may be viewed as its subset. Visualization tools include charts, graphs, and presentations.

Machine learning might be the most well-known aspect of data science. Technologies like deep learning are at the core of AI development, enabling machines to learn from limited data input. Recently, great advances were made in unsupervised learning, which doesn’t require human input at all.

Big data refers to processing and analyzing large amounts of information. Handling massive data volumes presents specific challenges in terms of computational capacity and error reduction.

Finally, statistics form one of the cornerstones of practical data science use. Statistical analysis is helpful in business, demographics, and numerous social and natural sciences. Reliable statistics help researchers create predictive models and projections, allowing for efficient planning down the line.

Benefits of Earning a Data Science Certificate or Degree

Getting a degree or certificate in data science offers you an edge both in professional improvement and in the job market. The very process of gaining credentials is an opportunity to learn and practice essential skills. Plus, you can build a respectful portfolio along the way.

A degree or certificate means better job opportunities. Every reputable employer in the field will want to see recognized credentials from their applicants, and that’s particularly true when hiring for better-paid positions.

If you’ve already got a starting-level job in data science, credentials from reputable institutions will help advance your career. That kind of growth also creates a potential for better salaries and work benefits.

Finally, once you enroll in a data science degree or certificate program, you’ll meet other people pursuing similar interests. This will be an excellent opportunity for networking. Combined with the credentials, your new network of colleagues can help you advance even further.

Tips for Choosing the Right Data Science Online Course or Program

When you start searching for the right program online, it’s vital to consider several factors:

  • The content and curriculum of the course
  • Instructor expertise and reputation in the industry
  • The duration of the program
  • How flexible the course is
  • Pricing and whether there are options for financial aid
  • Testimonials or reviews from previous students

Besides these considerations, you should account for your personal preferences. Define your goals and what you want to achieve with the program. Also, it’s important for the program to match the learning style that suits you the best.

Gain the Essential Skills for the Hottest Profession Today

Our data science course suggestions include a selection of programs from the most respected industry leaders. With the high-quality courses on offer, all you’ll need to do is pick the program that matches your career goals.

Today’s job market has a high demand for data science experts. Getting certified or earning a degree in the field will help you start a career easier, which is why you should consider this important move as soon as possible.

Related posts

The Yuan: AI is childlike in its capabilities, so why do so many people fear it?
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Nov 8, 2024 6 min read

Source:

  • The Yuan, Published on October 25th, 2024.

By Zorina Alliata

Artificial intelligence is a classic example of a mismatch between perceptions and reality, as people tend to overlook its positive aspects and fear it far more than what is warranted by its actual capabilities, argues AI strategist and professor Zorina Alliata.

ALEXANDRIA, VIRGINIA – In recent years, artificial intelligence (AI) has grown and developed into something much bigger than most people could have ever expected. Jokes about robots living among humans no longer seem so harmless, and the average person began to develop a new awareness of AI and all its uses. Unfortunately, however – as is often a human tendency – people became hyper-fixated on the negative aspects of AI, often forgetting about all the good it can do. One should therefore take a step back and remember that humanity is still only in the very early stages of developing real intelligence outside of the human brain, and so at this point AI is almost like a small child that humans are raising.

AI is still developing, growing, and adapting, and like any new tech it has its drawbacks. At one point, people had fears and doubts about electricity, calculators, and mobile phones – but now these have become ubiquitous aspects of everyday life, and it is not difficult to imagine a future in which this is the case for AI as well.

The development of AI certainly comes with relevant and real concerns that must be addressed – such as its controversial role in education, the potential job losses it might lead to, and its bias and inaccuracies. For every fear, however, there is also a ray of hope, and that is largely thanks to people and their ingenuity.

Looking at education, many educators around the world are worried about recent developments in AI. The frequently discussed ChatGPT – which is now on its fourth version – is a major red flag for many, causing concerns around plagiarism and creating fears that it will lead to the end of writing as people know it. This is one of the main factors that has increased the pessimistic reporting about AI that one so often sees in the media.

However, when one actually considers ChatGPT in its current state, it is safe to say that these fears are probably overblown. Can ChatGPT really replace the human mind, which is capable of so much that AI cannot replicate? As for educators, instead of assuming that all their students will want to cheat, they should instead consider the options for taking advantage of new tech to enhance the learning experience. Most people now know the tell-tale signs for identifying something that ChatGPT has written. Excessive use of numbered lists, repetitive language and poor comparison skills are just three ways to tell if a piece of writing is legitimate or if a bot is behind it. This author personally encourages the use of AI in the classes I teach. This is because it is better for students to understand what AI can do and how to use it as a tool in their learning instead of avoiding and fearing it, or being discouraged from using it no matter the circumstances.

Educators should therefore reframe the idea of ChatGPT in their minds, have open discussions with students about its uses, and help them understand that it is actually just another tool to help them learn more efficiently – and not a replacement for their own thoughts and words. Such frank discussions help students develop their critical thinking skills and start understanding their own influence on ChatGPT and other AI-powered tools.

By developing one’s understanding of AI’s actual capabilities, one can begin to understand its uses in everyday life. Some would have people believe that this means countless jobs will inevitably become obsolete, but that is not entirely true. Even if AI does replace some jobs, it will still need industry experts to guide it, meaning that entirely new jobs are being created at the same time as some older jobs are disappearing.

Adapting to AI is a new challenge for most industries, and it is certainly daunting at times. The reality, however, is that AI is not here to steal people’s jobs. If anything, it will change the nature of some jobs and may even improve them by making human workers more efficient and productive. If AI is to be a truly useful tool, it will still need humans. One should remember that humans working alongside AI and using it as a tool is key, because in most cases AI cannot do the job of a person by itself.

Is AI biased?

Why should one view AI as a tool and not a replacement? The main reason is because AI itself is still learning, and AI-powered tools such as ChatGPT do not understand bias. As a result, whenever ChatGPT is asked a question it will pull information from anywhere, and so it can easily repeat old biases. AI is learning from previous data, much of which is biased or out of date. Data about home ownership and mortgages, e.g., are often biased because non-white people in the United States could not get a mortgage until after the 1960s. The effect on data due to this lending discrimination is only now being fully understood.

AI is certainly biased at times, but that stems from human bias. Again, this just reinforces the need for humans to be in control of AI. AI is like a young child in that it is still absorbing what is happening around it. People must therefore not fear it, but instead guide it in the right direction.

For AI to be used as a tool, it must be treated as such. If one wanted to build a house, one would not expect one’s tools to be able to do the job alone – and AI must be viewed through a similar lens. By acknowledging this aspect of AI and taking control of humans’ role in its development, the world would be better placed to reap the benefits and quash the fears associated with AI. One should therefore not assume that all the doom and gloom one reads about AI is exactly as it seems. Instead, people should try experimenting with it and learning from it, and maybe soon they will realize that it was the best thing that could have happened to humanity.

Read the full article below:

Read the article
The European Business Review: Adapting to the Digital Age: Teaching Blockchain and Cloud Computing
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Nov 6, 2024 6 min read

Source:


By Lokesh Vij

Lokesh Vij is a Professor of BSc in Modern Computer Science & MSc in Applied Data Science & AI at Open Institute of Technology. With over 20 years of experience in cloud computing infrastructure, cybersecurity and cloud development, Professor Vij is an expert in all things related to data and modern computer science.

In today’s rapidly evolving technological landscape, the fields of blockchain and cloud computing are transforming industries, from finance to healthcare, and creating new opportunities for innovation. Integrating these technologies into education is not merely a trend but a necessity to equip students with the skills they need to thrive in the future workforce. Though both technologies are independently powerful, their potential for innovation and disruption is amplified when combined. This article explores the pressing questions surrounding the inclusion of blockchain and cloud computing in education, providing a comprehensive overview of their significance, benefits, and challenges.

The Technological Edge and Future Outlook

Cloud computing has revolutionized how businesses and individuals’ access and manage data and applications. Benefits like scalability, cost efficiency (including eliminating capital expenditure – CapEx), rapid innovation, and experimentation enable businesses to develop and deploy new applications and services quickly without the constraints of traditional on-premises infrastructure – thanks to managed services where cloud providers manage the operating system, runtime, and middleware, allowing businesses to focus on development and innovation. According to Statista, the cloud computing market is projected to reach a significant size of Euro 250 billion or even higher by 2028 (from Euro 110 billion in 2024), with a substantial Compound Annual Growth Rate (CAGR) of 22.78%. The widespread adoption of cloud computing by businesses of all sizes, coupled with the increasing demand for cloud-based services and applications, fuels the need for cloud computing professionals.

Blockchain, a distributed ledger technology, has paved the way by providing a secure, transparent, and tamper-proof way to record transactions (highly resistant to hacking and fraud). In 2021, European blockchain startups raised $1.5 billion in funding, indicating strong interest and growth potential. Reports suggest the European blockchain market could reach $39 billion by 2026, with a significant CAGR of over 47%. This growth is fueled by increasing adoption in sectors like finance, supply chain, and healthcare.

Addressing the Skills Gap

Reports from the World Economic Forum indicate that 85 million jobs may be displaced by a shift in the division of labor between humans and machines by 2025. However, 97 million new roles may emerge that are more adapted to the new division of labor between humans, machines, and algorithms, many of which will require proficiency in cloud computing and blockchain.

Furthermore, the World Economic Forum predicts that by 2027, 10% of the global GDP will be tokenized and stored on the blockchain. This massive shift means a surge in demand for blockchain professionals across various industries. Consider the implications of 10% of the global GDP being on the blockchain: it translates to a massive need for people who can build, secure, and manage these systems. We’re talking about potentially millions of jobs worldwide.

The European Blockchain Services Infrastructure (EBSI), an EU initiative, aims to deploy cross-border blockchain services across Europe, focusing on areas like digital identity, trusted data sharing, and diploma management. The EU’s MiCA (Crypto-Asset Regulation) regulation, expected to be fully implemented by 2025, will provide a clear legal framework for crypto-assets, fostering innovation and investment in the blockchain space. The projected growth and supportive regulatory environment point to a rising demand for blockchain professionals in Europe. Developing skills related to EBSI and its applications could be highly advantageous, given its potential impact on public sector blockchain adoption. Understanding the MiCA regulation will be crucial for blockchain roles related to crypto-assets and decentralized finance (DeFi).

Furthermore, European businesses are rapidly adopting digital technologies, with cloud computing as a core component of this transformation. GDPR (Data Protection Regulations) and other data protection laws push businesses to adopt secure and compliant cloud solutions. Many European countries invest heavily in cloud infrastructure and promote cloud adoption across various sectors. Artificial intelligence and machine learning will be deeply integrated into cloud platforms, enabling smarter automation, advanced analytics, and more efficient operations. This allows developers to focus on building applications without managing servers, leading to faster development cycles and increased scalability. Processing data closer to the source (like on devices or local servers) will become crucial for applications requiring real-time responses, such as IoT and autonomous vehicles.

The projected growth indicates a strong and continuous demand for blockchain and cloud professionals in Europe and worldwide. As we stand at the “crossroads of infinity,” there is a significant skill shortage, which will likely increase with the rapid adoption of these technologies. A 2023 study by SoftwareOne found that 95% of businesses globally face a cloud skills gap. Specific skills in high demand include cloud security, cloud-native development, and expertise in leading cloud platforms like AWS, Azure, and Google Cloud. The European Commission’s Digital Economy and Society Index (DESI) highlights a need for improved digital skills in areas like blockchain to support the EU’s digital transformation goals. A 2023 report by CasperLabs found that 90% of businesses in the US, UK, and China adopt blockchain, but knowledge gaps and interoperability challenges persist.

The Role of Educational Institutions

This surge in demand necessitates a corresponding increase in qualified individuals who can design, implement, and manage cloud-based and blockchain solutions. Educational institutions have a critical role to play in bridging this widening skills gap and ensuring a pipeline of talent ready to meet the demands of this burgeoning industry.

To effectively prepare the next generation of cloud computing and blockchain experts, educational institutions need to adopt a multi-pronged approach. This includes enhancing curricula with specialized programs, integrating cloud and blockchain concepts into existing courses, and providing hands-on experience with leading technology platforms.

Furthermore, investing in faculty development to ensure they possess up-to-date knowledge and expertise is crucial. Collaboration with industry partners through internships, co-teach programs, joint research projects, and mentorship programs can provide students with invaluable real-world experience and insights.

Beyond formal education, fostering a culture of lifelong learning is essential. Offering continuing education courses, boot camps, and online resources enables professionals to upskill or reskill and stay abreast of the latest advancements in cloud computing. Actively promoting awareness of career paths and opportunities in this field and facilitating connections with potential employers can empower students to thrive in the dynamic and evolving landscape of cloud computing and blockchain technologies.

By taking these steps, educational institutions can effectively prepare the young generation to fill the skills gap and thrive in the rapidly evolving world of cloud computing and blockchain.

Read the full article below:

Read the article