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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Expert Pierluigi Casale analyzes the adoption of AI by companies, the ethical and regulatory challenges and the differentiated approach between large companies and SMEs

By Gianni Rusconi

Easier said than done: to paraphrase the well-known proverb, and to place it in the increasingly large collection of critical issues and opportunities related to artificial intelligence, the task that CEOs and management have to adequately integrate this technology into the company is indeed difficult. Pierluigi Casale, professor at OPIT (Open Institute of Technology, an academic institution founded two years ago and specialized in the field of Computer Science) and technical consultant to the European Parliament for the implementation and regulation of AI, is among those who contributed to the definition of the AI ​​Act, providing advice on aspects of safety and civil liability. His task, in short, is to ensure that the adoption of artificial intelligence (primarily within the parliamentary committees operating in Brussels) is not only efficient, but also ethical and compliant with regulations. And, obviously, his is not an easy task.

The experience gained over the last 15 years in the field of machine learning and the role played in organizations such as Europol and in leading technology companies are the requirements that Casale brings to the table to balance the needs of EU bodies with the pressure exerted by American Big Tech and to preserve an independent approach to the regulation of artificial intelligence. A technology, it is worth remembering, that implies broad and diversified knowledge, ranging from the regulatory/application spectrum to geopolitical issues, from computational limitations (common to European companies and public institutions) to the challenges related to training large-format language models.

CEOs and AI

When we specifically asked how CEOs and C-suites are “digesting” AI in terms of ethics, safety and responsibility, Casale did not shy away, framing the topic based on his own professional career. “I have noticed two trends in particular: the first concerns companies that started using artificial intelligence before the AI ​​Act and that today have the need, as well as the obligation, to adapt to the new ethical framework to be compliant and avoid sanctions; the second concerns companies, like the Italian ones, that are only now approaching this topic, often in terms of experimental and incomplete projects (the expression used literally is “proof of concept”, ed.) and without these having produced value. In this case, the ethical and regulatory component is integrated into the adoption process.”

In general, according to Casale, there is still a lot to do even from a purely regulatory perspective, due to the fact that there is not a total coherence of vision among the different countries and there is not the same speed in implementing the indications. Spain, in this regard, is setting an example, having established (with a royal decree of 8 November 2023) a dedicated “sandbox”, i.e. a regulatory experimentation space for artificial intelligence through the creation of a controlled test environment in the development and pre-marketing phase of some artificial intelligence systems, in order to verify compliance with the requirements and obligations set out in the AI ​​Act and to guide companies towards a path of regulated adoption of the technology.

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CCN: Australia Tightens Crypto Oversight as Exchanges Expand, Testing Industry’s Appetite for Regulation
OPIT - Open Institute of Technology
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  • CCN, published on March 29th, 2025

By Kurt Robson

Over the past few months, Australia’s crypto industry has undergone a rapid transformation following the government’s proposal to establish a stricter set of digital asset regulations.

A series of recent enforcement measures and exchange launches highlight the growing maturation of Australia’s crypto landscape.

Experts remain divided on how the new rules will impact the country’s burgeoning digital asset industry.

New Crypto Regulation

On March 21, the Treasury Department said that crypto exchanges and custody services will now be classified under similar rules as other financial services in the country.

“Our legislative reforms will extend existing financial services laws to key digital asset platforms, but not to all of the digital asset ecosystem,” the Treasury said in a statement.

The rules impose similar regulations as other financial services in the country, such as obtaining a financial license, meeting minimum capital requirements, and safeguarding customer assets.

The proposal comes as Australian Prime Minister Anthony Albanese’s center-left Labor government prepares for a federal election on May 17.

Australia’s opposition party, led by Peter Dutton, has also vowed to make crypto regulation a top priority of the government’s agenda if it wins.

Australia’s Crypto Growth

Triple-A data shows that 9.6% of Australians already own digital assets, with some experts believing new rules will push further adoption.

Europe’s largest crypto exchange, WhiteBIT, announced it was entering the Australian market on Wednesday, March 26.

The company said that Australia was “an attractive landscape for crypto businesses” despite its complexity.

In March, Australia’s Swyftx announced it was acquiring New Zealand’s largest cryptocurrency exchange for an undisclosed sum.

According to the parties, the merger will create the second-largest platform in Australia by trading volume.

“Australia’s new regulatory framework is akin to rolling out the welcome mat for cryptocurrency exchanges,” Alexander Jader, professor of Digital Business at the Open Institute of Technology, told CCN.

“The clarity provided by these regulations is set to attract a wave of new entrants,” he added.

Jader said regulatory clarity was “the lifeblood of innovation.” He added that the new laws can expect an uptick “in both local and international exchanges looking to establish a foothold in the market.”

However, Zoe Wyatt, partner and head of Web3 and Disruptive Technology at Andersen LLP, believes that while the new rules will benefit more extensive exchanges looking for more precise guidelines, they will not “suddenly turn Australia into a global crypto hub.”

“The Web3 community is still largely looking to the U.S. in anticipation of a more crypto-friendly stance from the Trump administration,” Wyatt added.

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