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SmartData Collective > Exclusive > How CIS Credentials Can Launch Your AI Development Career
ExclusiveNews

How CIS Credentials Can Launch Your AI Development Career

CIS graduates have a strong foundation to build successful careers in artificial intelligence.

Ryan Ayers
Ryan Ayers
10 Min Read
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christina wocintechchat com 6dv3pe jnsg unsplash
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Something that we like talking about on Smart Data Collective is how people can turn their computer information systems (CIS) background into real careers in artificial intelligence. You are entering a field where demand is climbing fast and the skill gap is widening. It is the kind of shift that favors people who already know how software, data, and networks interact. You just need to focus on a few specific steps to apply those skills in AI projects. This is one of the things that humans can still do better than AI.

Contents
Learning AI Fundamentals Through a CIS LensWhy Credentials MatterIdentifying Your Experiential KnowledgePathways to Credentialing Practical Experience1. Industry Certifications2. Prior Learning Assessment (PLA) for Degree Programs3. Building a Demonstrative PortfolioTips for Success

You are not alone if you’re thinking about this career direction. There are thousands of developers looking for ways to use AI tools every day. Stack Overflow Insights reports that 76% of all developers surveyed are either using or planning to use AI in their workflow this year. Keep reading to learn more.

Learning AI Fundamentals Through a CIS Lens

You are already ahead if you’ve worked with systems design, databases, and networking in school or on the job. There are CIS graduates who just need to add machine learning and data modeling to their toolkit. It is helpful to start with Python and learn how to use libraries like TensorFlow or PyTorch. You can then move on to supervised and unsupervised learning techniques.

You are not just writing code—you’re solving problems that depend on context. There are cases where a CIS-trained person can build recommendation engines, fraud detection systems, or chatbots. It is helpful to partner with teams in healthcare, finance, or retail to find use cases. You bring more to the table when you understand both systems and the data flow behind AI.

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You are stepping into a sector that’s expected to expand rapidly. There are projections from the UN Trade and Development that show AI demand growing 25 times between 2023 and 2033. It is hard to ignore how fast this field is scaling compared to most other areas in tech. You can prepare now and have a real advantage over time.

You are in a stronger position when you have a credential that backs up your technical knowledge. There are many online programs now offering AI concentrations on top of CIS foundations. It is smart to look at courses from places like Google, Coursera, or IBM. You don’t need a master’s degree if you’ve got a CIS background and targeted certifications.

You are not limited to research labs or big tech firms anymore. There are over 1,897,100 software engineers in the U.S. today, according to the Bureau of Labor Statistics. It is growing by 17% a year, which is much faster than most jobs, and AI is a major reason for the increase. The growing need for big data is another. You can apply for roles like AI engineer, ML operations specialist, or backend developer with AI integration.

You are more likely to get hired if you have real examples of your work. There are websites like GitHub where you can upload your AI projects, even if they’re small. It is helpful to document how you used datasets, what the goal was, and what the model achieved. You are more likely to get callbacks when recruiters can see your thinking in action.

You are building a career that gives you a lot of room to grow. There are very few fields where CIS knowledge translates so well into a new specialty like AI. It is often the people with practical systems experience who do best in this space. You just have to be willing to keep learning.

In the dynamic and ever-evolving world of Computer Information Systems (CIS), practical, hands-on experience is often touted as the most valuable asset. While this holds true, a curious paradox exists: many employers still heavily rely on formal credentials —degrees and certifications— as primary filters in the hiring process. This can leave seasoned professionals, whose knowledge was forged in the trenches of real-world projects, feeling overlooked.

The good news is that a wealth of experience is not just valuable, it can be strategically leveraged and transformed into the credentials that open new doors. This article explores how to turn career experience— whether as an IT auditor or a software engineer—  into credentials for the CIS workforce.

Why Credentials Matter

While your on-the-job learning is gold, credentials serve several crucial functions in the modern CIS landscape and allow potential or current employers the peace of mind that comes from great workmanship.

  • HR Gatekeepers: Automated Applicant Tracking Systems (ATS) and human HR screeners often use keywords derived from job descriptions, including specific certifications or degree requirements. Without these, your resume might not even reach the hiring manager.
  • Standardized Baseline: Credentials provide a standardized, verifiable baseline of knowledge. An employer knows that someone with a CompTIA Security+ certification possesses a certain level of foundational cybersecurity knowledge, regardless of where or how they gained parts of it.

Identifying Your Experiential Knowledge

Before you can credential your experience, you need to be able to articulate it. This requires a systematic self-assessment:

  1. Inventory Your Projects & Responsibilities: List every significant project you’ve worked on, outlining your specific role, the technologies used (software, hardware, cloud platforms, programming languages), and the problems you solved.
  2. Translate Tasks into Skills: Don’t just say you “managed servers.” Instead, break it down: “Configured and maintained Windows Server 2019 environments,” “Implemented Active Directory Group Policies,” “Automated patch management using PowerShell scripts.”
  3. Quantify Your Impact: Whenever possible, use numbers. “Reduced network downtime by 15%,” “Managed a budget of $X,” “Supported Y number of users,” “Deployed Z cloud instances.”

Pathways to Credentialing Practical Experience

Once you’ve cataloged your skills, here are the primary avenues for formalizing them:

1. Industry Certifications

This is often the most direct and cost-effective way to credential specific technical skills. Many certifications are designed to validate practical knowledge:

  • Vendor-Neutral: CompTIA (A+, Network+, Security+, CySA+), ISC2 (CISSP), ISACA (CISM, CISA). These validate broad knowledge applicable across various technologies.
  • Vendor-Specific: Microsoft (Azure, M365), Cisco (CCNA, CCNP), AWS, Google Cloud, Red Hat. These focus on expertise with particular platforms or products.

Select certifications that align directly with your current skills and future career goals. Leverage your experience to accelerate your study. Many certifications don’t require specific experience; they just require passing a rigorous exam.

2. Prior Learning Assessment (PLA) for Degree Programs

Many universities, particularly online and competency-based institutions, offer Prior Learning Assessment (PLA) or Experiential Learning Credits for prior learning. This allows you to submit a portfolio, take a challenge exam, or demonstrate competencies gained through work experience for college credit.

  • Benefits: Reduces the time and cost of earning a degree.
  • Examples: Institutions like Western Governors University (WGU) are built around competency-based learning, allowing students to accelerate degrees based on existing knowledge.

Strategy: Research universities that offer PLA or competency-based programs. Prepare a detailed portfolio of your work experience, aligning it with course objectives.

3. Building a Demonstrative Portfolio

While not a “credential” in the traditional sense, a robust portfolio is irrefutable proof of your capabilities, often outweighing mere certifications on a resume. This is especially vital for roles in software development, data science, cybersecurity, and cloud architecture.

Strategy: Dedicate time to building projects that showcase your skills. Document your process thoroughly. Even if your work experience is proprietary, create similar projects on public platforms to demonstrate your mastery.

Tips for Success

  • Strategic Selection: Choose credentials that are most relevant to your career trajectory and that directly validate your most valuable practical skills.
  • Network: Connect with others in your field. They can offer advice on valuable certifications, share study tips, and even open doors to opportunities.

Your career experience is an invaluable asset. By strategically transforming it into recognized credentials, you not only validate your expertise but also empower yourself to navigate the competitive CIS job market with confidence, opening doors to new opportunities and continued professional growth.

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ByRyan Ayers
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Ryan Ayers has consulted a number of Fortune 500 companies within multiple industries including information technology and big data. After earning his MBA in 2010, Ayers also began working with start-up companies and aspiring entrepreneurs, with a keen focus on data collection and analysis.

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