Your future in computing

1. A degree opens several kinds of work

You do not have to choose your permanent specialization in your first semester. Begin by discovering which problems hold your attention. Do you enjoy explaining a puzzling failure, organizing information, building something physical, understanding mathematical models, or finding out what a user actually needs? Different roles combine these interests in different proportions.

A job title is only a starting point. Two people called “software engineer” may spend their days doing very different work. Read the responsibilities, ask what the team produces, and look for the skills used to make decisions. Computing also happens inside hospitals, factories, banks, transport systems and public services—not only inside companies that sell software.

Technical product roles, solutions engineering and entrepreneurship offer further possibilities. Some roles involve substantial customer communication; others require deeper specialization or postgraduate study. They are not shortcuts around technical understanding. Use the ACM overview of computing work as another starting point, then investigate actual teams and current role descriptions.

2. Choose a team, not just a company label

A small startup can give a junior person broad responsibility and direct contact with decisions. It can also lack time for supervision. A large organization may provide structured training and specialist colleagues, while placing you in a narrow role. Neither description is universal. An excellent mentor in a small team may be more valuable than a famous name with little support.

Consultancies may involve changing clients and delivery deadlines. Corporate IT connects technology with an organization's internal operations. Research laboratories emphasize investigation and evidence. Public institutions have their own service responsibilities and procedures. Ask about the actual manager, work and expectations rather than treating organization size as a measure of quality.

“Culture” becomes meaningful when translated into behaviour: How are mistakes discussed? Is asking for help welcomed? Are deadlines negotiated? How are overtime and availability handled? What happens when a student has an examination? Listen for specific examples rather than slogans such as “we are a family.”

3. Build work you can explain

A beginner can have credible evidence without paid employment. A modest course project, a student-club contribution or a carefully documented experiment can show how you think. The strongest example is often one you understand deeply, including what went wrong. Ten copied repositories do not explain your ability as clearly as one project you can demonstrate and discuss.

For example, a fictional temperature-monitor project is more than “used Arduino.” Its story might be: read sensor values, reject malformed records on the PC, calculate a status and save a log. Explain which part you implemented, which library or skeleton was supplied, and how you tested values near the threshold. If only simulated data were used, say so. Do not turn a classroom demonstration into a claim of a certified safety system.

A useful repository includes a short problem statement, setup instructions, a diagram or photograph, expected output, a few tests and known limitations. A screenshot can show the result, but instructions should let another person reproduce it. Identify teammates and reused components. Keep credentials, personal data and confidential employer material out of public repositories.

4. Express yourself clearly

A professional introduction is a short explanation of where you are, what interests you, what evidence you can discuss and what you are looking for. It is not your complete life history. Practise a version of roughly a minute, then adapt it to the listener. Explain a project differently to a recruiter, an embedded engineer and a nontechnical customer.

“I am a first-year computer engineering student interested in how software interacts with devices. In a course project I worked on validating sensor records and testing boundary cases. I am still developing my C skills, and I would like to learn how an engineering team reviews and tests real systems.”

This fictional introduction is specific without pretending to be expert. Compare it with “I am hardworking, passionate and a team player.” Those qualities may be true, but an example helps another person understand them. A technical explanation should connect the problem, your action and the result before listing tool names.

Practise in both Turkish and English. Clear sentences, attentive listening and a willingness to clarify matter more than adopting impressive jargon. Ask a friend to summarize what they understood. If their summary is wrong, revise the explanation rather than blaming the listener.

A professional email needs a meaningful subject, a brief introduction, a specific reason for contacting that person and a manageable request. For an informational conversation, ask about their work and entry route rather than immediately asking them to obtain a job for you. Respect a refusal or a lack of time.

5. A résumé makes claims you must support

A first résumé can be short. For many beginner applications, one well-organized page is a useful target, not a universal rule. Follow the employer’s instructions and the conventions of the destination. In Türkiye, “CV” is often used for this application document; an academic CV may instead contain a longer history of research and publications.

Keep a private master record of education, projects and experience, then select the relevant evidence for each application. Use plain headings and readable text. Check the exported PDF, filenames, links and contact details. Automated application systems differ; do not rely on hidden keywords or tricks. MIT’s career-writing guidance provides examples of résumés, portfolios and professional correspondence.

Replace “helped with a project” with an accurate action and result. Add a number only when you can support it. A small verified result is better than an invented percentage. You may describe a nontechnical job when it demonstrates responsibility, communication or coordination.

6. Understand recruitment and HR

Hiring is a process involving people with different responsibilities. A recruiter may coordinate applications and assess basic fit. A hiring manager considers the team’s needs. Technical interviewers investigate your reasoning and knowledge. HR may handle employment processes, compensation arrangements and onboarding. In a small organization, one person may perform several of these roles.

Read a job advertisement as a description to investigate, not a personal verdict. Distinguish essential eligibility conditions from a longer wish list. If you meet the core requirements and can explain relevant evidence, you can consider applying without claiming every listed skill. Keep a simple application record so that you remember the role, contact, dates and next action.

Professional conduct includes keeping appointments, warning someone promptly about a delay, asking clear questions and treating everyone respectfully. HR is neither an obstacle to defeat nor your private adviser: it operates within the employer’s responsibilities and constraints. Ask who can answer a technical, scheduling or compensation question. Request important commitments in writing.

Before accepting a position, understand its role, supervisor, location, hours, pay arrangements and start date. Read the documents rather than relying on an informal promise. University internship approval and employment requirements depend on the arrangement; obtain current guidance from the relevant university office or a qualified adviser when needed.

7. Interviews are conversations with evidence

Prepare by reading about the role, reviewing your own projects and practising explanation aloud. During a technical question, clarify the inputs and expected result, work through a small example, and discuss assumptions before proposing a solution. Explain how you would test it. Silence followed by an unexplained answer hides useful reasoning.

When you do not know something, distinguish what you know from what you would investigate. “I have not used that library; I would begin with its input contract and a small example” is more credible than bluffing. If AI tools are allowed, clarify the rules and explain how you verify their output. If they are not allowed, respect that condition.

For a teamwork question, a simple structure is situation, task, action and result. Suppose a group’s sensor log was intermittently empty. Explain the context, your responsibility, how you reproduced the failure and what changed after your fix. Include the contribution of others. The result may be a better test or a discovered limitation, not a dramatic success.

Interview the employer too: “What would a successful first month look like?”, “Who reviews a beginner’s work?”, “How is feedback given?”, and “How do you accommodate a student’s examination schedule?” A rejection does not establish that you lack ability. Review what you can improve, request feedback politely where appropriate, and continue applying without treating any single outcome as a diagnosis of your future.

8. Look for internships that help you learn

An internship lets you investigate whether you enjoy the daily work of an area, not merely its public image. Notice how tasks are assigned, changes reviewed, tests selected and disagreements resolved. Ask what you can learn from an experienced colleague’s decision. A placement may also reveal an area you do not want to pursue, which is useful information.

Before accepting, ask about a named supervisor, a realistic project, the schedule, feedback and the resources provided. Berkeley’s internship guidance similarly emphasizes structured learning, mentorship and meaningful work. Its local administrative rules are not GTÜ rules; check your department’s current requirements for approval and documentation.

Keep a short private learning log: the task, what you tried, what you learned and what remains unclear. Ask permission before publishing screenshots, code, device photographs or data. A public portfolio can explain the general problem and your contribution without disclosing company information. Obtain a referee’s permission before giving out their contact details.

9. Protect your education when working

Paid work can provide income, confidence and relevant experience. It can also expand beyond its original promise. By the third and fourth years, a job may begin to consume the time needed for advanced courses, laboratories and projects. Early employment is not a substitute for completing the foundations that support a longer career.

A job that repeatedly prevents you from attending classes and laboratories may cost more than the income shown on the offer. Agree on a workable timetable before accepting, and revisit it when the reality changes.

Some students need income; the answer cannot simply be “do not work.” Consider predictable shifts, summer work, work closer to campus, or fewer agreed hours where feasible. Discuss constraints with your adviser and employer early. Ask explicitly about class times, examination periods, travel, remote availability and whether “part-time” includes messages and meetings outside the stated hours.

In this example, increasing work from 12 to 24 hours uses another 12 hours, but only 8 were unallocated. At least 4 hours must be removed from something else even before unexpected demands. A total that fits also does not resolve overlapping appointments: a Tuesday shift cannot occupy the same hours as a compulsory lecture.

Watch for repeated absences, unfinished assignments, loss of sleep and a job that keeps exceeding its agreed hours. Treat these as reasons to renegotiate the arrangement or seek advice, not proof that you should simply try harder. Preserve learning and health as real constraints when comparing opportunities.

10. Compare offers and discuss compensation

Salary matters. So do the hours required to earn it, travel, the supervisor, learning opportunities and compatibility with your studies. Decide which conditions are necessary and which are preferences before an attractive name or headline amount dominates your judgement. Berkeley’s offer-evaluation guide recommends comparing an offer with your own criteria and clarifying missing information.

Under these assumptions, B’s higher monthly pay comes with twice the agreed hours and unresolved conflicts. That does not make every higher-paid position a poor choice; it shows why the comparison must use your actual constraints. Missing information is a reason to ask, not a reason to invent a favourable answer.

Compensation conversations differ between organizations. A large graduate scheme may use fixed bands; a small firm may negotiate directly with a founder. Ask about the role’s range, what can be discussed and when pay is reviewed. Clarify the currency, payment period, gross versus net basis and which benefits are guaranteed before comparing figures. Do not invent another offer or turn the conversation into a threat.

“Thank you for the offer. I am interested in the work. Could we discuss the compensation range and the agreed weekly hours? I need to preserve my Tuesday classes. If the salary is fixed, is there flexibility in the schedule or a defined review after an initial period?”

Respectful language can adapt to company culture without giving up legitimate questions. A confident discussion is compatible with courtesy. Request the agreed terms in writing and ask for reasonable time to consider them. A promise of future equity or a possible bonus is different from guaranteed salary; ask for an explanation instead of treating it as cash already earned.

11. AI and your future in computing

AI can make you a more capable engineer. This course encourages you to approach it with curiosity rather than fear. Tools that help you explore an idea, understand an unfamiliar interface or draft a solution can expand what you are able to attempt. The important question is how to use that assistance while developing your own understanding.

Generating a program is one task within a job. Engineering also includes discovering what people need, defining acceptable failures, choosing tradeoffs, integrating components, testing real behaviour and explaining decisions. A convincing answer to the wrong problem does not become useful simply because it was generated quickly.

It would be misleading to promise that no role will disappear or that every employer will hire in the same way. Tasks, expectations and entry routes can change. Equally, a claim that a tool can perform part of a task is not proof that an occupation will vanish. The ILO’s 2025 analysis assesses potential exposure to generative AI and emphasizes transformation of work as the more likely broad outcome, rather than wholesale replacement. It is a global assessment, not a guarantee about a particular computing job.

Why the fundamentals still help

If you understand arrays and memory, you can question a generated program that accesses an invalid element. If you understand networks, you can distinguish an application error from a connection failure. If you understand learning and evaluation, you can ask whether a model was tested on genuinely new examples. These concepts make you an informed user of assistance instead of a passenger waiting for an answer.

Consider the sensor project again. An AI tool drafts a parser, but its output silently accepts a record with a missing value. You define the valid format, supply a malformed test case, inspect the result and repair the behaviour. You then discover that simulated data do not test the real device’s timing. This is engineering work: the useful result comes from the combination of assistance, knowledge and verification.

Try a problem yourself, ask for a hint or an alternative explanation, and then check whether you can solve a related problem without assistance. Use tools within the course AI guidelines and an employer’s rules. Do not upload confidential code, personal records or private interview material without permission. Follow the stated rules during assessments and interviews.

Your goal is not to beat a machine at producing the most lines of code. It is to become someone who can understand a problem, work with others and deliver a result that deserves trust. Build a combination of fundamentals, domain knowledge, communication and responsible tool use. You can prepare for changing work without accepting either panic or the promise that nothing will change.

12. A plan you can revise

A career plan is a sequence of useful experiments. It should give you direction without pretending you already know the final destination. Revisit it when a course, project or conversation changes your interests. You do not need an expensive certificate or a polished public profile before beginning.

For your next small step, choose one role to investigate, one project to explain and one person whose experience you would like to understand. Draft an introduction. Identify a gap you can work on during the next month. These are optional self-study suggestions, not new submissions or grading requirements.

Keep curiosity and professional honesty together. Ask for help, give credit, accept useful feedback and share what you learn appropriately. Your first role does not need to define the whole career. The ability to learn from a real problem and communicate your reasoning will remain useful as tools and opportunities change.