Data visualization is an essential skill in all areas of business and industry. The ability to take complex data and present it in a simple way speeds up decision-making and increases business agility. No wonder so many tech professionals are considering upskilling themselves with an online data visualization course.
If you’re a graduate looking for the best data visualization courses online, you might consider the Open Institute of Technology (OPIT). OPIT offers a Master’s Degree (MSc) in Responsible AI that includes a full segment on data analytics and visualization within the context of AI and other data sciences.
Let’s take a look at more reasons to start an online data visualization course and the benefits it can bring.
The Power of Data Visualization
Businesses thrive on high-quality data. The world generates 463 exabytes of data daily, much of which flows through busy organizations. While experienced data scientists may be able to gain snapshot analyses from complex datasets, most people can’t. That’s where data visualization comes into its own.
A data science and visualization course teaches students how to collect, cleanse, and analyze data before visualization transformations. This includes turning data into graphs, maps, or other graphic displays.
Data visualization turns raw data into usable insights. These insights allow business leaders to take action, change marketing campaigns, budget allocations, or even hiring policies. The ability to quickly see what needs to change allows businesses to edge ahead of competitors.
Choosing the Right Data Visualization Course
The best courses for data visualization teach these skills without taking busy IT professionals or data managers away from their current careers. Online courses provide flexibility and accessibility, allowing learners to study when it’s convenient for them.
Consider the following factors when choosing data visualization online courses:
- Duration
- Topics covered
- Support and student community
- Accreditation
- Career-aligned skills
- Certification
OPIT’s online courses cater to professionals with busy schedules by providing a high-level curriculum entirely online. OPIT is also fully EU-accredited and provides students with internationally recognized qualifications.
The Best Data Visualization Online Courses
Choosing data analysis and visualization courses online is tricky with so many options available. Here are five of the best currently available. Always take the above points on choosing the best online data visualization course into account before committing to a program of study.
Data Visualization with Python
This course from IBM via the Coursera platform looks exclusively at how to use the Python programming language for data analysis and visualization. Classed as intermediate level, some basic data management and programming knowledge is assumed. Tech professionals may find this course useful for upskilling themselves and learning some foundational data visualization skills.
Provider: IBM
Duration: 19 hours
Fees: $39 per month which includes access to other related courses
Qualification Gained: Digital course-specific certificate
Data Visualization Nanodegree Program
Udacity presents this “nanodegree” as a collection of four courses. The program introduces and then expands on data visualization and storytelling. Students will learn design principles, how to use Tableau, dashboard planning and design, and how to build a data story. There are also topics on data limitations and biases.
Provider: Udacity
Duration: Five months
Fees: Either month-to-month at $249 or four months for $846 (minimum $1,095)
Qualification Gained: Udacity Certificate of Achievement
Data Storytelling for Business
One of the few hybrid courses on our list, this storytelling and data visualization course does offer the option for an in-person class. However, you can also complete the program over two virtual seminars, each lasting three hours. This short course focuses on the three “Ds” of data storytelling: Define, Draft, Display, De-clutter, and Direct. It focuses primarily on helping business professionals deliver more effective, impactful presentations.
Provider: StoryIQ
Duration: One day in-person or six hours online with a follow-up session after four weeks
Fees: $230
Qualification Gained: Digital certificate of completion
Hands-On Tableau Training for Data Science
Tech professionals who want to get more out of Tableau could sign up for this software-specific data visualization online course. Tableau is a popular platform for creating data dashboards and is often used for business intelligence (BI) purposes. Students will learn about different types of visuals including charts, maps, graphs, and tables, with table calculations. There’s also a deeper dive into data aggregation and granularity.
Provider: Udemy
Duration: There are nine hours of lectures to complete at your own pace
Fees: $99 for this course but the platform has various subscription options available
Qualification Gained: Udemy Certificate of Completion
OPIT MSc in Responsible AI
For those searching for the best courses on data visualization for graduates, a master’s degree is usually the next step. OPIT’s Master’s Degree in Responsible Artificial Intelligence covers multiple AI-related topics, including data analysis and visualization. Students learn about the challenges associated with handling large, complex datasets. They cover data preprocessing, cleaning, and using that data to tell effective stories.
Provider: OPIT (EU-accredited higher education provider)
Duration: The fast-track option takes 12 months and the standard pathway takes 18 months
Fees: €6,500 — scholarships and discounts are available
Qualification Gained: Globally recognized MSc, equivalent to a Level 7 qualification worth 90-120 ECTS
Key Components of a Comprehensive Data Visualization Course
How do you choose which course is right for you? Your search should start by deciding why you want to take a data science and visualization course. If it’s simply for the joy of studying and learning new skills, one of the shorter courses might suit you. However, if you’re a graduate working in tech already, upskilling yourself will probably require investing in an MSc or similar-level course.
Here are some advanced topics tech professionals to look out for:
- Exploratory data analysis
- Crafting data pipelines in multiple programming languages
- Handling intricate datasets
- Data cleansing, processing, and integration
- Creating visualizations from multiple streams of data
- Linear and nonlinear dimensionality reduction
These skills can help you get ahead in your career by giving you the tools to work with data in any organization. Advanced data science skills are transferable and system agnostic, allowing you to apply for more roles at higher salaries.
OPIT’s Approach to Data Visualization Education
Why study with OPIT? Our unique teaching methods and course structure are deliberately career-aligned. We want to support busy professionals moving forward on their chosen trajectory. The best data visualization courses should allow you to work at your own pace, around your existing commitments.
Our teaching faculty is packed with top-notch academic leaders. We believe that choosing the right team makes the differences between good and great education. On the OPIT MSc in Responsible AI course, for example, you get to learn from Panagiota Katsikouli, a computer science researcher at the University of Copenhagen. Other top-flight faculty members include Pierluigi Casale, a principal data officer for TomTom, and Raj Dasgupta, an AI/ML research scientist at US Naval Research Laboratory.
Your course structure will include a balance of theory and practical hands-on activities. Students start with foundational theory, and then quickly learn how to apply this in real-life situations. For data visualization, expect to start with collating and cleansing data and move on to advanced analysis and presentation techniques. All courses are competency-based, with no final exams to stress about. You acquire new skills as you progress, making these courses ideal for career-minded tech professionals.
Integrating Data Visualization With Other Data Science Skills
Data visualization isn’t a standalone skill. That’s why integrating it with other data science topics such as AI and machine learning is essential. You want a skillset you can apply within your career, which means learning how it relates to various other aspects of data management. Data analysis is normally a primary step in effective visualization. However, analysis isn’t possible without first collating and processing data. The best data analysis and visualization online courses should naturally teach students how data visualization works with other data skills.
OPIT’s courses achieve this by empowering students to create industry-relevant data dashboards, pipelines, and stories. The MSc course culminates with a thesis, which is a research endeavor related to the student’s career ambitions. Learners are also encouraged to pursue internships to practice their skills and gain experience to help them achieve their career goals.
Make Sure You Choose the Right Online Data Visualization Course for Your Career
Choosing the best online data visualization course is essential to optimize your time and learn relevant skills. Make sure you understand the time commitment, cost, and qualifications you’ll gain at the end.
It’s also important to make sure you choose a trusted, accredited educational provider. OPIT’s accredited online programs could take you one step closer to your professional goals.
Explore the OPIT course offerings for more information on how we can further your tech career.
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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.
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Source:
- The European Business Review, Published on October 27th, 2024.
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.
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