Algorithms are the essence of data mining and machine learning – the two processes 60% of organizations utilize to streamline their operations. Businesses can choose from several algorithms to polish their workflows, but the decision tree algorithm might be the most common.
This algorithm is all about simplicity. It branches out in multiple directions, just like trees, and determines whether something is true or false. In turn, data scientists and machine learning professionals can further dissect the data and help key stakeholders answer various questions.
This only scratches the surface of this algorithm – but it’s time to delve deeper into the concept. Let’s take a closer look at the decision tree machine learning algorithm, its components, types, and applications.
What Is Decision Tree Machine Learning?
The decision tree algorithm in data mining and machine learning may sound relatively simple due to its similarities with standard trees. But like with conventional trees, which consist of leaves, branches, roots, and many other elements, there’s a lot to uncover with this algorithm. We’ll start by defining this concept and listing the main components.
Definition of Decision Tree
If you’re a college student, you learn in two ways – supervised and unsupervised. The same division can be found in algorithms, and the decision tree belongs to the former category. It’s a supervised algorithm you can use to regress or classify data. It relies on training data to predict values or outcomes.
Components of Decision Tree
What’s the first thing you notice when you look at a tree? If you’re like most people, it’s probably the leaves and branches.
The decision tree algorithm has the same elements. Add nodes to the equation, and you have the entire structure of this algorithm right in front of you.
- Nodes – There are several types of nodes in decision trees. The root node is the parent of all nodes, which represents the overriding message. Chance nodes tell you the probability of a certain outcome, whereas decision nodes determine the decisions you should make.
- Branches – Branches connect nodes. Like rivers flowing between two cities, they show your data flow from questions to answers.
- Leaves – Leaves are also known as end nodes. These elements indicate the outcome of your algorithm. No more nodes can spring out of these nodes. They are the cornerstone of effective decision-making.
Types of Decision Trees
When you go to a park, you may notice various tree species: birch, pine, oak, and acacia. By the same token, there are multiple types of decision tree algorithms:
- Classification Trees – These decision trees map observations about particular data by classifying them into smaller groups. The chunks allow machine learning specialists to predict certain values.
- Regression Trees – According to IBM, regression decision trees can help anticipate events by looking at input variables.
Decision Tree Algorithm in Data Mining
Knowing the definition, types, and components of decision trees is useful, but it doesn’t give you a complete picture of this concept. So, buckle your seatbelt and get ready for an in-depth overview of this algorithm.
Overview of Decision Tree Algorithms
Just as there are hierarchies in your family or business, there are hierarchies in any decision tree in data mining. Top-down arrangements start with a problem you need to solve and break it down into smaller chunks until you reach a solution. Bottom-up alternatives sort of wing it – they enable data to flow with some supervision and guide the user to results.
Popular Decision Tree Algorithms
- ID3 (Iterative Dichotomiser 3) – Developed by Ross Quinlan, the ID3 is a versatile algorithm that can solve a multitude of issues. It’s a greedy algorithm (yes, it’s OK to be greedy sometimes), meaning it selects attributes that maximize information output.
- 5 – This is another algorithm created by Ross Quinlan. It generates outcomes according to previously provided data samples. The best thing about this algorithm is that it works great with incomplete information.
- CART (Classification and Regression Trees) – This algorithm drills down on predictions. It describes how you can predict target values based on other, related information.
- CHAID (Chi-squared Automatic Interaction Detection) – If you want to check out how your variables interact with one another, you can use this algorithm. CHAID determines how variables mingle and explain particular outcomes.
Key Concepts in Decision Tree Algorithms
No discussion about decision tree algorithms is complete without looking at the most significant concept from this area:
Entropy
As previously mentioned, decision trees are like trees in many ways. Conventional trees branch out in random directions. Decision trees share this randomness, which is where entropy comes in.
Entropy tells you the degree of randomness (or surprise) of the information in your decision tree.
Information Gain
A decision tree isn’t the same before and after splitting a root node into other nodes. You can use information gain to determine how much it’s changed. This metric indicates how much your data has improved since your last split. It tells you what to do next to make better decisions.
Gini Index
Mistakes can happen, even in the most carefully designed decision tree algorithms. However, you might be able to prevent errors if you calculate their probability.
Enter the Gini index (Gini impurity). It establishes the likelihood of misclassifying an instance when choosing it randomly.
Pruning
You don’t need every branch on your apple or pear tree to get a great yield. Likewise, not all data is necessary for a decision tree algorithm. Pruning is a compression technique that allows you to get rid of this redundant information that keeps you from classifying useful data.
Building a Decision Tree in Data Mining
Growing a tree is straightforward – you plant a seed and water it until it is fully formed. Creating a decision tree is simpler than some other algorithms, but quite a few steps are involved nevertheless.
Data Preparation
Data preparation might be the most important step in creating a decision tree. It’s comprised of three critical operations:
Data Cleaning
Data cleaning is the process of removing unwanted or unnecessary information from your decision trees. It’s similar to pruning, but unlike pruning, it’s essential to the performance of your algorithm. It’s also comprised of several steps, such as normalization, standardization, and imputation.
Feature Selection
Time is money, which especially applies to decision trees. That’s why you need to incorporate feature selection into your building process. It boils down to choosing only those features that are relevant to your data set, depending on the original issue.
Data Splitting
The procedure of splitting your tree nodes into sub-nodes is known as data splitting. Once you split data, you get two data points. One evaluates your information, while the other trains it, which brings us to the next step.
Training the Decision Tree
Now it’s time to train your decision tree. In other words, you need to teach your model how to make predictions by selecting an algorithm, setting parameters, and fitting your model.
Selecting the Best Algorithm
There’s no one-size-fits-all solution when designing decision trees. Users select an algorithm that works best for their application. For example, the Random Forest algorithm is the go-to choice for many companies because it can combine multiple decision trees.
Setting Parameters
How far your tree goes is just one of the parameters you need to set. You also need to choose between entropy and Gini values, set the number of samples when splitting nodes, establish your randomness, and adjust many other aspects.
Fitting the Model
If you’ve fitted your model properly, your data will be more accurate. The outcomes need to match the labeled data closely (but not too close to avoid overfitting) if you want relevant insights to improve your decision-making.
Evaluating the Decision Tree
Don’t put your feet up just yet. Your decision tree might be up and running, but how well does it perform? There are two ways to answer this question: cross-validation and performance metrics.
Cross-Validation
Cross-validation is one of the most common ways of gauging the efficacy of your decision trees. It compares your model to training data, allowing you to determine how well your system generalizes.
Performance Metrics
Several metrics can be used to assess the performance of your decision trees:
Accuracy
This is the proximity of your measurements to the requested values. If your model is accurate, it matches the values established in the training data.
Precision
By contrast, precision tells you how close your output values are to each other. In other words, it shows you how harmonized individual values are.
Recall
Recall is the number of data samples in the desired class. This class is also known as the positive class. Naturally, you want your recall to be as high as possible.
F1 Score
F1 score is the median value of your precision and recall. Most professionals consider an F1 of over 0.9 a very good score. Scores between 0.8 and 0.5 are OK, but anything less than 0.5 is bad. If you get a poor score, it means your data sets are imprecise and imbalanced.
Visualizing the Decision Tree
The final step is to visualize your decision tree. In this stage, you shed light on your findings and make them digestible for non-technical team members using charts or other common methods.
Applications of Decision Tree Machine Learning in Data Mining
The interest in machine learning is on the rise. One of the reasons is that you can apply decision trees in virtually any field:
- Customer Segmentation – Decision trees let you divide customers according to age, gender, or other factors.
- Fraud Detection – Decision trees can easily find fraudulent transactions.
- Medical Diagnosis – This algorithm allows you to classify conditions and other medical data with ease using decision trees.
- Risk Assessment – You can use the system to figure out how much money you stand to lose if you pursue a certain path.
- Recommender Systems – Decision trees help customers find their next product through classification.
Advantages and Disadvantages of Decision Tree Machine Learning
Advantages:
- Easy to Understand and Interpret – Decision trees make decisions almost in the same manner as humans.
- Handles Both Numerical and Categorical Data – The ability to handle different types of data makes them highly versatile.
- Requires Minimal Data Preprocessing – Preparing data for your algorithms doesn’t take much.
Disadvantages:
- Prone to Overfitting – Decision trees often fail to generalize.
- Sensitive to Small Changes in Data – Changing one data point can wreak havoc on the rest of the algorithm.
- May Not Work Well with Large Datasets – Naïve Bayes and some other algorithms outperform decision trees when it comes to large datasets.
Possibilities are Endless With Decision Trees
The decision tree machine learning algorithm is a simple yet powerful algorithm for classifying or regressing data. The convenient structure is perfect for decision-making, as it organizes information in an accessible format. As such, it’s ideal for making data-driven decisions.
If you want to learn more about this fascinating topic, don’t stop your exploration here. Decision tree courses and other resources can bring you one step closer to applying decision trees to your work.
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From the same author
Read the articleLife is unpredictable. While many of us have specific hopes and expectations of how our futures will turn out, things don’t always go as expected. There are many variables and unexpected incidents that can interfere and force you to alter your plans, and this is particularly true when it comes to education.
For instance, you might have had plans to study a specific subject, but had to deviate from those plans due to unforeseen circumstances. Or you may have had to enter the workforce in an occupation different from the one you sought in an effort to earn an income, a move that may not provide you with the time or opportunity to achieve your desired educational aims.
In short, every individual’s career pathway is different, and very few go exactly as we expect from the outset. Fortunately, even if you experience a few false starts or sudden twists in your pathway, there are always options available to help you get back on track.
The Unpredictable Nature of Education
In theory, the educational process seems simple. You select a course of study that interests you from the vast array of subjects and prospective professions, select the appropriate classes, acquire the knowledge and skills you need to succeed, and then embark on your profession.
In reality, however, as many people know from firsthand experience, the road to education is often far from straightforward. Here are just some of the many challenges that can take your educational path in a completely different direction:
- Life’s Curveballs: As touched on in the introduction, life is impossible to predict. Financial hardships, health issues, and family emergencies are just some of the unfortunate occurrences that might derail even the most perfectly planned educational regime.
- Changing Interests: People’s desires and preferences don’t necessarily stay the same throughout their entire lives. As you grow, learn, and have new experiences, your interests may change, and so, too, may your educational objectives.
- Pressure and Burnout: Some academic paths are particularly challenging, demanding intense levels of study and hard work. This can sometimes prove too much to bear, even for the most resilient students.
- Failures and Setbacks: Conventional education largely builds around tests and examinations, requiring students to demonstrate their competencies repeatedly. It’s a system that doesn’t suit everyone, and test failures can lead to setbacks and delays.
- Inequality: People can be born with very different privileges and levels of access to education. Those in certain parts of the world may find it much more challenging to complete their education path for financial, cultural, or even political reasons.
- Late Bloomers: People develop at different paces. Some may struggle educationally early on in their lives, forcing them to make certain concessions or sacrifices related to their studies, only to find their feet later in life once they’ve entered the world of work.
Whether you’re a late bloomer, have had your educational aspirations delayed by personal problems, desire to learn new skills and try something different, or want to begin a fresh chapter in your professional life, the Open Institute of Technology (OPIT) may be able to help.
Introducing OPIT
OPIT is an online teaching platform, making high-level technological educational programs accessible to all, no matter their age or background. Offering education in fields like computer science, artificial intelligence, and digital business, OPIT provides a curated collection of degrees. In addition, they offer classes taught by world-leading tutors imparting the wisdom and skills students need to achieve their goals and become the tech leaders of tomorrow.
Meanwhile, for those who have had somewhat tumultuous or unpredictable educational paths, OPIT offers the perfect course corrector: the OPIT Foundation Year.
The OPIT Foundation Year
OPIT’s Foundation Year is a Pre-Tertiary Certificate in Information Technology, fully aligned with MQF/EQF Level 4 standards and valued at 60 ECTS credits. Lasting just one year, this program essentially serves as a comprehensive yet accessible springboard towards higher-level education, creating a path towards degrees and careers in dynamic, flexible fields, like computer science and digital business.
Like other OPIT programs, the Foundation Year is delivered entirely online via the OPIT Virtual Learning Environment. Combining live lectures, asynchronous content, and interactive assessments, students enjoy diverse and dynamic study experiences, acquiring core skills like academic writing, mathematics, and computer literacy, and building a bedrock of knowledge and confidence before taking their next steps.
Who Is the Foundation Program For?
The Foundation Program is designed to provide a solid base upon which to build the technological education many students need. It’s the perfect choice for those who are eager and ambitious to enter professions in AI, data science, and computing, but don’t feel that they have the necessary core skills and knowledge needed to dive straight into a degree.
Entry requirements are relatively relaxed in order to allow as many students as possible to enjoy the benefits of this program. With that said, applicants should ideally hold an MQF/EQF Level 3 or equivalent qualification, with the intention of pursuing a bachelor’s degree. A minimum of B2 level of English proficiency is also required, as this is the working and studying language of the institution.
What the Foundation Year Provides
Perhaps you’ve recently graduated, are considering a career change, or finally have the opportunity to return to education after initial delays or unexpected disruptions to your original plans. Either way, the Foundation Year can help you enjoy:
- Greater Self-Confidence: Foundation Year graduates gain the fundamental skills they need to enter degree programs with much more self-belief and assuredness.
- Superior Tech Knowledge: Lasting two terms, this course explores mathematics, academic reading and writing, and provides an introduction to computer hardware and software.
- Foundational Mathematics: Mathematics literacy forms a large part of the study focus for the Foundation Year, helping students feel more comfortable with numbers and formulas.
- Flexible Learning: Unlike more rigid, conventional education environments, OPIT gives you the freedom and flexibility to study at a pace that suits you best, all from the comfort of home.
- Global Community: OPIT is an international institution, with staff and students from all around the world eager to share knowledge, exchange ideas, and help one another.
Take Your Next Steps to Success With the OPIT Foundation Year
If you’re curious about a career in technology or have always wanted to work with AI, data, and computers, but struggled to find the time and opportunities you need to acquire relevant skills and knowledge, the Foundation Program was made for people like you.
It’s the ideal entry point into the exciting world of online education, and the perfect first step towards a prestigious degree from an innovative and increasingly successful institution. Download the brochure to learn more about it, or start your online application, today.
Read the articleStudents today have a broader range of fields of study to choose from than ever before, but with the world becoming increasingly technological and computers increasing in influence and importance, pursuing a career in computer science often proves a smart, strategic choice.
There are numerous benefits and career paths associated with studying and working in computer science, and we’ll be listing just a few of them in this guide.
High Average Salaries
With the rising cost of living in many parts of the world, it’s unsurprising that many students are thinking several decades ahead to determine what level of starting salaries they could obtain in different career fields.
Many are also seeking professions that offer the opportunity for growth and the ability to advance up the ranks over time, thus increasing their salary and their quality of life in the process.
If a strong, stable salary with the opportunity for improved income is one of your top career priorities, computer science should be at or near the top of your list of prospective careers.
According to recent data, computer scientists earn an average of over €65,000 per year, with certain jobs, like IT project leader and data scientist, paying ever higher. Starting salaries are strong, too, with graduates earning anywhere from €46,000 to €60,000, depending on their chosen profession and level of qualifications.
There are similarly high average salaries reported around the world in computer science and related fields such as data science and AI/ML engineering. These numbers are projected to increase in the years to come, pointing to computer science as a way for graduates to get off to the best financial start of any career.
Unrivaled Flexibility
A common problem with some subjects and courses is that they only provide graduates with a narrow set of skills and a similarly narrow range of potential professions to which they can apply those skills.
That’s not the case with computer science. Graduates in this field can enjoy instant access to a remarkably diverse array of career opportunities, with even newer opportunities being created all the time as technology evolves and innovations emerge.
A few of the many industries and roles you might choose to enter in the field of computer science include:
- Healthcare: As a software developer, data analyst, or cybersecurity expert
- Finance: As a fintech engineer, blockchain developer, or security analyst
- Media: As a graphics programmer, AI developer, or game developer
- Education: As an analyst, software developer, or machine learning engineer
Guaranteed Opportunities
Some career paths are more limited than others, with relatively low numbers of opportunities, recurring risks of job loss, or difficulty obtaining employment in the first place.
Again, with computer science, this simply isn’t the case. At a time when 75% of companies plan to embrace AI and other technologies by 2027, and businesses of all sizes and industries are now relying on computers more than ever before, computer science graduates can enjoy almost unbeatable job security.
Opportunities will continue to grow for people with good computing knowledge, whether that be in the obvious fields like software and web development, engineering, and AI development, or more niche sectors.
With so many options, you’re effectively guaranteed a long, rewarding career if you put in the necessary time and effort needed to establish a strong foundation of computing skills.
Rapidly Expanding and Evolving Industries
It’s no secret that the world of technology is a dynamic and fast-moving one. In the past 20 years alone, we’ve seen the proliferation of the internet, the rapid advancement of smartphones and wearable devices, the emergence of AI, and so much more.
In the years ahead, engineers and developers will continue to explore the boundaries of modern technology’s powers and potential, driving new innovations and improvements and opening more exciting job opportunities for those already established and experienced in this field.
Getting into computer science now could therefore provide a solid foundation for a career filled with excitement as you uncover and explore new ways of working with computers in fields as diverse as healthcare, finance, education, entertainment, manufacturing, logistics, and beyond.
Start Your Computer Science Career at OPIT
We’ve discussed some of the many benefits associated with careers in computer science, from the high starting salaries to the rapidly growing array of job options available to graduates. By now, you may be eager to follow this particular career path and take advantage of the wealth of opportunities.
If you’re wondering how to start, the Open Institute of Technology (OPIT) may hold the answers you need. As an exclusively online learning platform, specializing in computer science and digital business, and staffed by some of the world’s leading tech experts, OPIT is producing the tech leaders of tomorrow.
Some of the many advantages of learning with OPIT include:
- Accessible and flexible online education that matches your learning style and schedule
- Heavy focus on real-world applications of the skills you acquire
- An international community of like-minded students from around the globe
- A top team of tutors and lecturers from varying fields and industries
- Progressive assessment of skills and understanding – not constant exams
OPIT offers a small, curated selection of courses for those seeking to gain the technological skills and knowledge to succeed in their chosen areas of expertise. That includes a BSc (Hons) in Computer Science – a six-term program, worth 180 ECTS credits.
Numerous IT industry leaders and experts helped develop this fully accredited undergraduate degree, which is online and accessible to all. Like other OPIT courses, it offers a flexible learning program, with progressive assessments, fast-track options, and the opportunity to be part of a growing community of learners and tutors.
If the benefits of doing a career in computer science interest you, download the OPIT BSc in Computer Science brochure or fill out an online application today and take your first step toward a rewarding and fulfilling profession.
-
Go to all authors
Related posts
Life is unpredictable. While many of us have specific hopes and expectations of how our futures will turn out, things don’t always go as expected. There are many variables and unexpected incidents that can interfere and force you to alter your plans, and this is particularly true when it comes to education.
For instance, you might have had plans to study a specific subject, but had to deviate from those plans due to unforeseen circumstances. Or you may have had to enter the workforce in an occupation different from the one you sought in an effort to earn an income, a move that may not provide you with the time or opportunity to achieve your desired educational aims.
In short, every individual’s career pathway is different, and very few go exactly as we expect from the outset. Fortunately, even if you experience a few false starts or sudden twists in your pathway, there are always options available to help you get back on track.
The Unpredictable Nature of Education
In theory, the educational process seems simple. You select a course of study that interests you from the vast array of subjects and prospective professions, select the appropriate classes, acquire the knowledge and skills you need to succeed, and then embark on your profession.
In reality, however, as many people know from firsthand experience, the road to education is often far from straightforward. Here are just some of the many challenges that can take your educational path in a completely different direction:
- Life’s Curveballs: As touched on in the introduction, life is impossible to predict. Financial hardships, health issues, and family emergencies are just some of the unfortunate occurrences that might derail even the most perfectly planned educational regime.
- Changing Interests: People’s desires and preferences don’t necessarily stay the same throughout their entire lives. As you grow, learn, and have new experiences, your interests may change, and so, too, may your educational objectives.
- Pressure and Burnout: Some academic paths are particularly challenging, demanding intense levels of study and hard work. This can sometimes prove too much to bear, even for the most resilient students.
- Failures and Setbacks: Conventional education largely builds around tests and examinations, requiring students to demonstrate their competencies repeatedly. It’s a system that doesn’t suit everyone, and test failures can lead to setbacks and delays.
- Inequality: People can be born with very different privileges and levels of access to education. Those in certain parts of the world may find it much more challenging to complete their education path for financial, cultural, or even political reasons.
- Late Bloomers: People develop at different paces. Some may struggle educationally early on in their lives, forcing them to make certain concessions or sacrifices related to their studies, only to find their feet later in life once they’ve entered the world of work.
Whether you’re a late bloomer, have had your educational aspirations delayed by personal problems, desire to learn new skills and try something different, or want to begin a fresh chapter in your professional life, the Open Institute of Technology (OPIT) may be able to help.
Introducing OPIT
OPIT is an online teaching platform, making high-level technological educational programs accessible to all, no matter their age or background. Offering education in fields like computer science, artificial intelligence, and digital business, OPIT provides a curated collection of degrees. In addition, they offer classes taught by world-leading tutors imparting the wisdom and skills students need to achieve their goals and become the tech leaders of tomorrow.
Meanwhile, for those who have had somewhat tumultuous or unpredictable educational paths, OPIT offers the perfect course corrector: the OPIT Foundation Year.
The OPIT Foundation Year
OPIT’s Foundation Year is a Pre-Tertiary Certificate in Information Technology, fully aligned with MQF/EQF Level 4 standards and valued at 60 ECTS credits. Lasting just one year, this program essentially serves as a comprehensive yet accessible springboard towards higher-level education, creating a path towards degrees and careers in dynamic, flexible fields, like computer science and digital business.
Like other OPIT programs, the Foundation Year is delivered entirely online via the OPIT Virtual Learning Environment. Combining live lectures, asynchronous content, and interactive assessments, students enjoy diverse and dynamic study experiences, acquiring core skills like academic writing, mathematics, and computer literacy, and building a bedrock of knowledge and confidence before taking their next steps.
Who Is the Foundation Program For?
The Foundation Program is designed to provide a solid base upon which to build the technological education many students need. It’s the perfect choice for those who are eager and ambitious to enter professions in AI, data science, and computing, but don’t feel that they have the necessary core skills and knowledge needed to dive straight into a degree.
Entry requirements are relatively relaxed in order to allow as many students as possible to enjoy the benefits of this program. With that said, applicants should ideally hold an MQF/EQF Level 3 or equivalent qualification, with the intention of pursuing a bachelor’s degree. A minimum of B2 level of English proficiency is also required, as this is the working and studying language of the institution.
What the Foundation Year Provides
Perhaps you’ve recently graduated, are considering a career change, or finally have the opportunity to return to education after initial delays or unexpected disruptions to your original plans. Either way, the Foundation Year can help you enjoy:
- Greater Self-Confidence: Foundation Year graduates gain the fundamental skills they need to enter degree programs with much more self-belief and assuredness.
- Superior Tech Knowledge: Lasting two terms, this course explores mathematics, academic reading and writing, and provides an introduction to computer hardware and software.
- Foundational Mathematics: Mathematics literacy forms a large part of the study focus for the Foundation Year, helping students feel more comfortable with numbers and formulas.
- Flexible Learning: Unlike more rigid, conventional education environments, OPIT gives you the freedom and flexibility to study at a pace that suits you best, all from the comfort of home.
- Global Community: OPIT is an international institution, with staff and students from all around the world eager to share knowledge, exchange ideas, and help one another.
Take Your Next Steps to Success With the OPIT Foundation Year
If you’re curious about a career in technology or have always wanted to work with AI, data, and computers, but struggled to find the time and opportunities you need to acquire relevant skills and knowledge, the Foundation Program was made for people like you.
It’s the ideal entry point into the exciting world of online education, and the perfect first step towards a prestigious degree from an innovative and increasingly successful institution. Download the brochure to learn more about it, or start your online application, today.
Students today have a broader range of fields of study to choose from than ever before, but with the world becoming increasingly technological and computers increasing in influence and importance, pursuing a career in computer science often proves a smart, strategic choice.
There are numerous benefits and career paths associated with studying and working in computer science, and we’ll be listing just a few of them in this guide.
High Average Salaries
With the rising cost of living in many parts of the world, it’s unsurprising that many students are thinking several decades ahead to determine what level of starting salaries they could obtain in different career fields.
Many are also seeking professions that offer the opportunity for growth and the ability to advance up the ranks over time, thus increasing their salary and their quality of life in the process.
If a strong, stable salary with the opportunity for improved income is one of your top career priorities, computer science should be at or near the top of your list of prospective careers.
According to recent data, computer scientists earn an average of over €65,000 per year, with certain jobs, like IT project leader and data scientist, paying ever higher. Starting salaries are strong, too, with graduates earning anywhere from €46,000 to €60,000, depending on their chosen profession and level of qualifications.
There are similarly high average salaries reported around the world in computer science and related fields such as data science and AI/ML engineering. These numbers are projected to increase in the years to come, pointing to computer science as a way for graduates to get off to the best financial start of any career.
Unrivaled Flexibility
A common problem with some subjects and courses is that they only provide graduates with a narrow set of skills and a similarly narrow range of potential professions to which they can apply those skills.
That’s not the case with computer science. Graduates in this field can enjoy instant access to a remarkably diverse array of career opportunities, with even newer opportunities being created all the time as technology evolves and innovations emerge.
A few of the many industries and roles you might choose to enter in the field of computer science include:
- Healthcare: As a software developer, data analyst, or cybersecurity expert
- Finance: As a fintech engineer, blockchain developer, or security analyst
- Media: As a graphics programmer, AI developer, or game developer
- Education: As an analyst, software developer, or machine learning engineer
Guaranteed Opportunities
Some career paths are more limited than others, with relatively low numbers of opportunities, recurring risks of job loss, or difficulty obtaining employment in the first place.
Again, with computer science, this simply isn’t the case. At a time when 75% of companies plan to embrace AI and other technologies by 2027, and businesses of all sizes and industries are now relying on computers more than ever before, computer science graduates can enjoy almost unbeatable job security.
Opportunities will continue to grow for people with good computing knowledge, whether that be in the obvious fields like software and web development, engineering, and AI development, or more niche sectors.
With so many options, you’re effectively guaranteed a long, rewarding career if you put in the necessary time and effort needed to establish a strong foundation of computing skills.
Rapidly Expanding and Evolving Industries
It’s no secret that the world of technology is a dynamic and fast-moving one. In the past 20 years alone, we’ve seen the proliferation of the internet, the rapid advancement of smartphones and wearable devices, the emergence of AI, and so much more.
In the years ahead, engineers and developers will continue to explore the boundaries of modern technology’s powers and potential, driving new innovations and improvements and opening more exciting job opportunities for those already established and experienced in this field.
Getting into computer science now could therefore provide a solid foundation for a career filled with excitement as you uncover and explore new ways of working with computers in fields as diverse as healthcare, finance, education, entertainment, manufacturing, logistics, and beyond.
Start Your Computer Science Career at OPIT
We’ve discussed some of the many benefits associated with careers in computer science, from the high starting salaries to the rapidly growing array of job options available to graduates. By now, you may be eager to follow this particular career path and take advantage of the wealth of opportunities.
If you’re wondering how to start, the Open Institute of Technology (OPIT) may hold the answers you need. As an exclusively online learning platform, specializing in computer science and digital business, and staffed by some of the world’s leading tech experts, OPIT is producing the tech leaders of tomorrow.
Some of the many advantages of learning with OPIT include:
- Accessible and flexible online education that matches your learning style and schedule
- Heavy focus on real-world applications of the skills you acquire
- An international community of like-minded students from around the globe
- A top team of tutors and lecturers from varying fields and industries
- Progressive assessment of skills and understanding – not constant exams
OPIT offers a small, curated selection of courses for those seeking to gain the technological skills and knowledge to succeed in their chosen areas of expertise. That includes a BSc (Hons) in Computer Science – a six-term program, worth 180 ECTS credits.
Numerous IT industry leaders and experts helped develop this fully accredited undergraduate degree, which is online and accessible to all. Like other OPIT courses, it offers a flexible learning program, with progressive assessments, fast-track options, and the opportunity to be part of a growing community of learners and tutors.
If the benefits of doing a career in computer science interest you, download the OPIT BSc in Computer Science brochure or fill out an online application today and take your first step toward a rewarding and fulfilling profession.
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