Santiago frequently shares insights about computer science on social media. In July 2023, he shared a computer science curriculum with his 415,000 followers.
This curriculum is designed for individuals who can dedicate approximately 20 hours per week to completing a computer science course independently over two years.
Santiago noted that the curriculum aligns precisely with the degree requirements of an undergraduate computer science major and comprises courses from leading academic institutions, as well as other reputable colleges.
The curriculum is divided into four sections: Introduction, where students can review the material and determine whether it meets their needs, and Core, which corresponds to the first three years of a college computer science program.
The Advanced section corresponds to the final year of a college computer science curriculum. In the Final Project section, students can validate, consolidate, and showcase their knowledge by completing a comprehensive project.
Santiago acknowledged that pursuing a curriculum like this independently can be challenging.
Having the support of professors and fellow students is essential, but with discipline and motivation, the provided materials can be valuable.
In July 2023, it was reported that around 85% of graduates from the Boise State College of Engineering’s Computer Science Department were employed by companies based in Idaho five years after completing their degrees.
This achievement highlighted the department’s significant role in contributing to the “brain gain” necessary to support the local industry.
A more recent analysis conducted by Boise State University “Computer Science Education in the Age of AI” has revealed that computer science graduates are experiencing a higher-than-normal unemployment rate in 2025, which exceeds 6%.
Despite this trend, the university maintains that a computer science degree remains valuable, especially as the importance of artificial intelligence (AI) continues to grow.
Insights from the Department of Computer Science at Boise State emphasize that large language models (LLMs) do not make computer science degrees obsolete, nor do they eliminate entry-level software developer positions.
The department’s findings indicate that jobs typically held by computer science graduates—such as software developer, software engineer, web developer, and mobile app developer—are evolving.
Many companies are realizing that replacing human workers with AI can be a misguided approach.
Boise State asserts that the actual value of a computer science degree lies in the proficient use of programming languages and tools, particularly those related to AI. Graduates must also possess a solid understanding of computer science fundamentals to develop successful products.
Professional software developers require a deep knowledge of computer programming to utilize LLMs effectively—it’s more than just casual coding.
Job opportunities are increasingly available in sectors such as healthcare, warehousing, automotive, and precision agriculture.
In this age of AI, mastery of core computer science concepts, including programming, algorithms, data structures, and mathematics, remains crucial.
While AI tools can automate many tasks, understanding the underlying principles is essential for practical application, customization, and innovation in AI systems.
Skills in Python, knowledge of machine learning algorithms, data modeling, and complex problem-solving are becoming increasingly valuable.
For those aiming to enter the tech field without a computer science degree, it is crucial to focus on building a solid foundation in core computer science concepts, gaining practical experience through projects, contributing to open-source initiatives, and obtaining relevant certifications.
Proficiency in languages such as Python, Java, or R is essential for working with AI tools and frameworks. Understanding algorithms and selecting the appropriate data structures for specific tasks are crucial for building efficient AI systems.
Knowledge of linear algebra, calculus, and statistics is vital for grasping the mathematical foundations of machine learning algorithms.
A solid understanding of core machine learning concepts, algorithms (such as neural networks), and frameworks (like TensorFlow or PyTorch) is essential for developing and deploying AI solutions.
Data collection, cleaning, and analysis are critical for training and evaluating AI models.
The ability to break down complex problems and develop logical solutions is a cornerstone of computer science and is highly valuable in AI development.
Principles of software engineering, including design, architecture, and testing, are fundamental for building robust and reliable AI systems.
With the increasing use of AI, it is crucial to understand the ethical implications and potential biases present in algorithms.
The field of AI is constantly evolving, so being adaptable to new technologies and committed to continuous learning is essential. Effective communication and teamwork are also crucial when developing and deploying AI solutions, especially when collaborating within interdisciplinary teams.
Here is a completely free Computer Science curriculum for those with the discipline to go through it independently.
The curriculum follows the same degree requirements as an undergraduate computer science major and consists of courses from Harvard, MIT, and Princeton, among… pic.twitter.com/lay6qQyT2s
— Santiago (@svpino) July 3, 2023
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