The Best AI Tools for Engineering Students (2026)

AI Tools for Engineering Students

Engineering graduate Alex Gornik recommends several AI tools that can save time on data analysis, coding projects, CAD prototyping, studying, and job preparation.

Google Colab with Gemini

Use Colab to explore datasets before starting coursework or projects. It can generate exploratory data analyses, including relevant charts and tables, without requiring a local coding setup. Colab also offers access to cloud GPUs for data science and machine-learning work. Gornik notes that Jupyter notebooks and Colab are used in industry.

AI Coding Agents: Google Antigravity and Cursor

Coding agents can help set up development environments, write code for larger projects, and build websites and user interfaces. Gornik highlights Antigravity’s ability to run a page locally, capture screenshots, and test interactions such as buttons.

Potential uses include hackathons, coursework, theses, personal projects, and creating a CV website. Gornik cautions against accepting generated code blindly, especially for serious projects or work where understanding the underlying computer science is important.

Zoo.dev

Zoo.dev receives an honorable mention as a text-to-CAD tool. Gornik has not tested it himself, but suggests it could help students quickly create simple prototypes, such as a custom enclosure for electronics, without extensive CAD skills.

NotebookLM

Gornik’s top recommendation is NotebookLM, a research and study assistant that can work with PDFs, lecture slides, documents, and videos. It can answer questions about these materials and create study resources.

He describes three main uses:

1. Lecture preparation: Upload course materials and relevant explanatory videos, then generate an audio overview to listen to before class. NotebookLM can also answer questions and create resources such as flashcards.
2. Literature reviews: Summarize research papers, explain difficult material in simpler terms, assess relevance to a thesis, and identify shared themes using tools such as mind maps or audio summaries. Gornik recommends checking its explanations against the original papers.
3. Job interviews: Gather company materials, job descriptions, website information, and details about interviewers to prepare, particularly for behavioral interviews and questions about company values.

Main Guidance

The video is a practical overview rather than a step-by-step software tutorial. Its main recommendations are to use Colab for understanding data, coding agents to speed up project setup and interface work while reviewing their output, Zoo.dev for quick CAD prototypes, and NotebookLM for lecture preparation, research, and interview preparation.

Main Speaker

• Alex Gornik — Presenter and engineering graduate sharing recommendations based on his studies and engineering work.