5 lời khuyên chọn ngành CNTT năm 2026

Summary

In this video, the speaker, an experienced professional in IT and AI, shares personal insights on choosing a career path and field of study in Vietnam. They emphasize that generic advice from others often lacks relevance, advocating for asking specific, targeted questions instead. The speaker encourages exploring interdisciplinary knowledge, combining IT with fields like business or finance, to increase adaptability and career opportunities. They caution against blindly following trends, instead suggesting venturing into emerging, less-popular fields for potential advantages. Additionally, the video introduces various AI and data science courses, from beginner Python to advanced deep learning, highlighting practical applications and essential mathematics for AI.

Takeaways

• 😀 Never ask others which field to choose, as their advice may not align with your personal strengths and goals.
• 😀 Your personal abilities, strengths, and interests should guide your career path, not the experiences of others.
• 😀 The job market is constantly changing, and predictions about which industries will thrive in 4-5 years are often uncertain.
• 😀 General advice from others, especially from people who don’t know you well, can be too vague to be helpful in your career decision-making.
• 😀 Instead of asking 'Which field should I choose?', ask specific questions about what skills are needed or what the industry requires.
• 😀 Specializing in only one area of IT might limit your career opportunities. A broader skillset across multiple fields will make you more competitive.
• 😀 Combining fields like AI with software engineering or IT with economics can open up diverse career opportunities and expand your skills.
• 😀 In Europe, dual-degree programs that combine IT with economics are growing in popularity, offering more career flexibility and marketability.
• 😀 Don't chase 'hot' fields just because they’re trending—career paths based on trends can leave you vulnerable to market shifts.
• 😀 University education doesn’t guarantee that you will end up working in the field you studied. The most important lesson is to develop self-learning skills and adapt as you progress.

Q & A

Why does the speaker advise against asking others which major to choose?

The speaker explains that everyone has different strengths, weaknesses, and starting points. Advice from others is often based on their personal experience and may not suit your unique skills or interests, making general guidance less useful.

What is the main reason predictions about future job market trends can be unreliable?

The job market changes continuously and unpredictably. Even experienced professionals cannot accurately forecast which fields will be in demand 4-5 years into the future.

How can asking specific questions improve the usefulness of advice received?

Specific questions, such as which skills to develop or which programming languages to learn, show focused interest and allow the advisor to provide tailored, actionable guidance relevant to your goals.

Why does the speaker suggest learning multiple fields instead of focusing on just one?

Learning multiple, complementary fields—like AI and software engineering—broadens career opportunities, enhances problem-solving skills, and makes you more competitive in a rapidly evolving tech industry.

Can students combine different learning methods to study multiple fields?

Yes, students can combine formal university programs with online courses or self-learning to study multiple fields, allowing flexibility and access to diverse knowledge without being confined to one curriculum.

What is the risk of choosing majors solely based on current popularity?

Majors that are popular today may not be in demand when students graduate. Following trends can lead to intense competition and fewer job opportunities, whereas leading trends early can provide a significant advantage.

Why does the speaker encourage exploring new or less popular fields?

Studying new or emerging fields can position students ahead of trends, giving them early access to opportunities that may become valuable in the future, despite the inherent uncertainty.

How does university education help beyond acquiring specific knowledge?

University education fosters self-learning, critical thinking, and time management. It also provides networking opportunities with peers and mentors, which can support career growth and adaptability in the future.

According to the speaker, how common is it for people to work in a field different from their major?

It is quite common; most people do not work in the exact field they studied at university. Education often serves as a foundation for learning new skills and adapting to different career paths.

What are some recommended beginner-level AI courses mentioned in the transcript?

The speaker mentions a Python and AI basic course for beginners without prior programming experience. This course introduces Python programming, relevant libraries for data and machine learning, and practical AI applications.

What advanced AI topics does the speaker suggest for students with prior experience?

For students with some programming background, the speaker suggests data science and machine learning courses, covering AI applications like natural language processing and computer vision, including private dataset projects for hands-on experience.

Why is learning mathematical foundations important for pursuing AI and machine learning?

Mathematical knowledge is essential to understand algorithms, model development, and data analysis. Strengthening math skills ensures students can effectively implement AI and machine learning techniques.