Jurusan Paling Dibutuhin di Era AI Ternyata Ini

Main Ideas

1. Data Science Is in Demand in the AI Era

The speakers argue that data science skills are needed across many industries, not just technology companies. As organizations increasingly use data to make decisions, demand is growing for people who can interpret and analyze it.

They describe a shortage of capable data analysts and data scientists in Indonesia compared with industry needs, creating potential career opportunities. They also stress that using AI effectively involves more than writing prompts or generating images and videos. Users need to understand the subject and know what data, analysis, or output is needed.

For data science, this means learning fundamentals such as data, statistics, analytical methods, and models. AI tools can assist, but users need enough knowledge to judge whether their results are relevant and correct. Data scientists also need domain knowledge: foundational skills can apply across sectors, but useful analysis and AI applications often need to be tailored to a specific field, such as education.

2. The Proposed Study Approach Combines Fundamentals With Specialization

Students would first build foundational skills, then develop expertise in a domain or industry they want to pursue. They may be able to choose from available specializations or propose an area of interest that is not already offered.

The speakers describe data science as useful both for people already working in a particular industry and for those who have not yet chosen a career field.

3. The Campus Aims to Connect Education With Employment

In response to concerns about whether a broad data science program would meet employers’ needs, the speakers note that many jobs do not require a narrowly defined degree. Understanding an industry and having relevant skills can be more important.

They describe a wider campus ecosystem that includes the job platform Lokerja.id, intended to connect local and global talent with potential opportunities. The speakers attribute the gap between job seekers and employers partly to mismatched skills and weak fundamentals, and say education should help address that mismatch.

Their broader ambition is not only to prepare employees, but also to support students who may want to become entrepreneurs.

4. Access, Flexibility, and Standards

An audience member who is a full-time caregiver asks whether the program could accommodate people with substantial work or family responsibilities. The speakers respond supportively, though the excerpt does not provide a detailed timetable or specific accessibility arrangements.

The campus intends to set meaningful graduation requirements rather than prioritize high or rapid graduation rates merely to improve accreditation results. The speakers acknowledge that students learn at different speeds and face different circumstances, including financial and academic challenges. They say administrative rules may allow some flexibility, but the transcript does not specify the exact policy.

They emphasize balancing accessibility with credible standards: the campus wants to make learning available to many people while ensuring graduates meet a genuine competency threshold.

5. Affordability and Alternative Pathways

The speakers say one motivation for establishing the campus is to provide an alternative that could put pressure on higher-education prices. They argue that more alternatives may limit excessive price increases.

They also describe a possible pathway for students preparing to retake the university entrance examination (UTBK): students could begin studying at the campus while continuing their preparation, then decide whether to continue or pursue another option.

6. Online Learning Depends on Teaching Quality, Not Just Format

Responding to concerns that online programs may teach only basic material or fail to sustain learning, a speaker argues that online education can work well when the pedagogy is effective.

Important factors include instructors’ ability to teach—not merely their command of the subject—as well as well-designed assignments, questions, and course structure. The speaker contrasts passive or poorly designed online classes with courses that require students to engage seriously and demonstrate their learning.

7. Fundamentals Should Not Be Skipped, but Learning Can Be Adaptive

The speakers say foundational knowledge is ideally built earlier in a student’s education, but catching up later is better than never learning it. They caution against assuming that subjects such as mathematics can simply be skipped, since gaps in fundamentals may become obstacles later.

At the same time, they describe the proposed system as adaptive: students who can demonstrate mastery may move ahead more quickly, while others can spend more time building the necessary foundation.

Speakers and Sources Featured

• Sabda PS — Panelist; discusses data science education, learning standards, accessibility, and fundamentals.
• Ferry Irwandi — Panelist; discusses demand for data skills, AI, employment, and online learning.
• Cania Citta — Panelist; contributes to the discussion. Her name is rendered as “Kania” in the subtitles.
• Unnamed audience member — Physics student from UIN Syarif Hidayatullah Jakarta, studying data science and machine learning; asks about data science prospects and specialization.
• Alvan — Audience member and caregiver; asks about access to lectures and job prospects.
• Rifki Muhammad Zin — Audience member and psychology student; asks about graduation standards, time limits, and differing student circumstances.
• Mona — Audience member, tutoring teacher, and education consultant; asks about online teaching, fundamentals, and critical thinking.
• Unnamed moderator/host — Manages the Q&A and closing segment.
• Malaka campus team members named during the closing — Bagas, Nanda, Daniel, Dia, Faisal, Yasmin, Tevi, Memet, and Tata.