Artificial Intelligence technologies are a cornerstone of current systems design and implementation. Our goal is to help match the ever increasing labor demand with industry supported community college efforts, creating model curriculum and providing professional development.
Course Name | Description | Program |
---|---|---|
Introduction to AI & Machine Learning | Artificial Intelligence (AI) basic concepts and Machine Learning (ML) techniques: Classification and Prediction, Natural Language Processing (NLP), Computer Vision (CV), Deep Learning (DL), AI project cycles, culture, and professional expectations. | Deep Learning Certificate, Natural Language Processing Certificate, Computer Vision Certificate, AI Degree |
Mathematics for AI | Linear Algebra, Probability & Statistics, and Calculus for Artificial. Math 100 can be replaced with {Math 13 + Math 3E + Math 3A} | Deep Learning Certificate, Natural Language Processing Certificate, Computer Vision Certificate, AI Degree |
Deep Learning I | Introduction to Deep Learning (DL): Machine Learning (ML), additional classification and regression methods, single-layer neural networks, multi-layer neural networks, training and improving deep networks. | Deep Learning Certificate, AI Degree |
Computer Vision I | Introduction to basic knowledge and skills of Computer Vision through image acquisition and processing using AI techniques and Python libraries. | Computer Vision Certificate, AI Degree |
Natural Language Processing I | Fundamental concepts in Natural Language Processing (NLP): Basic understanding of NLP and its applications, NLP models and algorithms, data sets and visualization techniques, and NLP programming tools. | Natural Language Processing Certificate, AI Degree |
Ethics and AI | Introduction to ethical implications and moral questions coming off from the development and implementation of artificial intelligence (AI): Data and Privacy, Opacity of AI Systems, Bias and Data Security, and others. | Deep Learning Certificate, Natural Language Processing Certificate, Computer Vision Certificate, AI Degree |
Python for Computational AI and Visualization | Basic understanding and practice of Python programming using computational Artificial Intelligence (AI) techniques and data, and performing data visualization using libraries (NumPy, MatplotLib, Seaborn, etc.). | Deep Learning Certificate, Natural Language Processing Certificate, Computer Vision Certificate, AI Degree |
Deep Learning II | Advanced Deep Learning (DL) algorithms and techniques: Generative Adversarial Networks (GAN), Deep Reinforcement Learning *Elective option for AI/AS Degree | Deep Learning Certificate, AI Degree |
Computer Vision II | Advanced Computer Vision (CV): Convolutional Neural Networks (CNNs), deep Convolutional Neural Networks (CNNs) with Visual Geometry Group (VGG) , OpenVINO, TensorFlow, OpenCV 3 & OpenCV 4. *Elective option for AI/AS Degree | Computer Vision Certificate, AI Degree |
Natural Language Processing II | Advanced Natural Language Processing (NLP): forefront technologies and techniques in testing and building applications through transformers and models. *Elective option for AI/AS Degree | Natural Language Processing Certificate, AI Degree |
AI/ML Capstone/Internship | AI Degree |
AWS ML Educator Enablement Program Manager
Intel AI Education Manager, Government Affairs
AWS Sr. ML Educator Enablement Program Manager
Intel Data Scientist
PayPal Data Scientist
BACCC has licensed from Intel the complete 2-year Artificial Intelligence instructional program. This material was developed in collaboration with Arizona Community Colleges. At no cost, any Bay Area college can adopt or adapt these materials for their own programs.
Five Bay Area faculty have already completed a Train-the-Trainer class. They will be conducting professional development activities to prepare colleges to use the model curriculum.
BACCC has developed partnerships with key industry organizations to support. In additional to the Intel materials, we have access to resources from other industry partners including: Alteryx, AWS, Google, IBM, Intel, and others.
In parallel to our curicular efforts, we will be working with IBM, CompTIA, and other industry standards developers. Our goal is to create entry-level certifications that lead to jobs for our students.
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Limited AI expertise or knowledge is identified as the biggest barrier to AI adoption by 39% of business leaders, according to Morning Consult’s IBM Global AI Index 2021
The 2020 LinkedIn U.S. Emerging Jobs Report identified the top 15 jobs over the previous five years and emphasized that “artificial intelligence and data science roles continue to proliferate across nearly every industry.” Artificial intelligence specialist (No. 1) showed 74% annual growth, and data scientist (No. 3) and data engineer (No. 8) followed with 37% and 33% annual growth.
“We must abandon the flawed idea that AI jobs are only for people with master’s degrees or PhDs with decades of experience.” – Forbes Aaron Burciaga
Average entry level Data Analytics jobs are $68,000/yr per Google
Most labor market reporting entities categorize Data Analytics and Artificial Intelligence jobs as Data Scientist positions, leading to the assumption that these are positions needing a lot of experience and education. Actually, there are many entry and mid level jobs where a certificate or Associate’s degree would suffice. Employers are realizing that in order to keep up with the workforce demand for AIDA they must build their workforce at the entry level, then train and promote from within. Here are some examples of entry and middle level skill AIDA jobs.
We anticipate having this ready for use by Spring 2023.
In addition to this web page, we will promote these offering to employers through newsletters, direct email, and social media through LinkedIn. Participating colleges will also promote to employers in their immediate area.
Employers are looking to the community colleges for diverse hires.
For planning purposes, we are projecting over a 4-year period, and assuming an average class size of 25 students. The AIDA project will have a positive impact on 3 kinds of students:
1) The 2-year-long Flagship Program will enroll 25 students in year 1, and another 25 in years 2, 3, and 4–a total of 100 students over 4 years.
2) Additional 2-year programs will be added with 2 other colleges in year 2, and another 4 colleges in year 3. That’s an additional 50 students in year 2, 100 more in year 3, and 300 students per year from all 6 colleges from year 4 onward. Over the 4-year planning period, these colleges will positively impact an additional 450 students.
3) Individual lessons and modules from the AI For Workforce curriculum will be incorporated into many existing courses. Our projection is for 6 of these course in year 1, 18 in year 2, then doubling each year to 36 in year 3, and 72 in year 4. With an average of 25 students per course, these 132 courses will provide a positive impact for another 3,300 students.
Combined, the AIDA project should positively impact a total of around 3,850 students over the first 4 years after launch.
We will be creating 4 weeklong professional development programs for both K12 and Community Colleges faculty.
We aim to promote curriculum that includes virtual, physical, and hybrid approaches.
Colleges are welcome to join this project. Involvement can range from providing release time for professional faculty development to investment from college-controlled Strong Workforce funding.
SWP college reps (you know who you are) can read more here.