Capability Tiers
The IALR Data Science Capability Maturity Model defines four tiers of capability. Learners progress from Foundations to Professional, raising the bar across five domains. Each chapter and lab on this site is tagged with the tier it builds.
Which tier am I?
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Writing Python
Git / version control
SQL
Training and evaluating ML models
Designing data pipelines / architecture
Tier 1
Data Science Foundations
Understands the concepts, interprets results, and runs existing notebooks. No coding required.
Tier 2
Data Science Practitioner
Works in Python, SQL, and Git. Builds and runs pipelines and models as directed.
Python Basics if-else and Flow Control Loops Functions Debugging Lists Dictionaries and Structuring Data Strings and Text Editing Regular Expressions Reading and Writing Files Organizing Files Command Line Programs Web Scraping Excel Spreadsheets Google Sheets SQLite Databases PDF and Word Documents CSV, JSON, and XML Files Time, Scheduling, and Launching Programs Sending Emails, Texts, and Push Notifications Graphs and Images Text in Images (OCR) Object-Oriented Programming Git and Version Control SQL for Data Science Testing and Unit Tests Communicating with Visualization Dataset Statistics and Visualization Feature Engineering Teen Mental Health Netflix Titles Catalog
Tier 3
Data Science Associate
Builds models with little oversight. Researches and implements algorithms and designs standard pipelines.
AI/ML Model Training CNNs and Computer Vision Transformers, RAG Models, and LLMs Model Evaluation Dimensionality Reduction Data Engineering and Pipelines Heart Disease Neural Networks CV Lab 01: Image Transforms and Augmentation CV Lab 02: Convolutions and Feature Maps CV Lab 03: Model Comparison and Metrics CV Lab 04: Grad-CAM Interpretability Fruit and Vegetable Classification
Tier 4
Data Science Professional
Architects scalable solutions, owns decisions, mentors the team, and communicates with stakeholders.
The full capability map
What each tier is expected to know or do, by domain. Use it to see where you are and what the next tier asks for. Linked capability names jump to where that skill is taught on the site.
Technical
| Capability | Tier 1 | Tier 2 | Tier 3 | Tier 4 |
|---|---|---|---|---|
| Programming Skills | None required | Python fundamentals; SQL familiarization | Python professional; SQL professional | Python fluency; SQL fluency |
| Algorithm Development | Familiar with common algorithm families and what they do (not the specifics) | Implement basic algorithms as directed | Solid understanding; can research and implement unfamiliar algorithms | Customize algorithms, implement quickly, and guide others |
| Algorithm Evaluation | Ask informed questions and interpret common performance outputs | Produce and interpret basic performance metrics across datasets | Produce and interpret all standard plus some custom metrics | Design, produce, and communicate model performance to stakeholders |
| Data Pipeline Development | Understands pipelines exist; not expected to develop them | Support pipeline implementation as instructed | Develop data pipelines with little oversight | Implement complex pipelines and advise the team |
| Algorithm & Pipeline Maintenance | Understands maintenance is needed; not expected to execute | Perform maintenance on algorithms and pipelines as directed | Understands maintenance strategies and can execute them | Leads and proactively manages maintenance |
| Git (Version Control) | None expected | Basic Git: clone, commit, push, merge | Git professional: standard plus some advanced commands | Git professional: resolves complex merge conflicts |
| Work Product | Runs and modifies existing notebooks; not expected to start from scratch | Works in Jupyter notebooks; runs and modifies as needed | Works in .py scripts and notebooks; starts from scratch to completion | Directs work from idea conception to completion |
Systems Architecture
| Capability | Tier 1 | Tier 2 | Tier 3 | Tier 4 |
|---|---|---|---|---|
| Solutions Architecture | None expected | None expected | Architect basic algorithm and data workflows | Architect efficient and scalable workflows |
| Algorithm Selection & Design | Understands families but not expected to select specific algorithms | Comfortable asking why a certain algorithm was selected | Adds input, questions decisions, and discusses design choices | Responsible for selection and confirming sound design |
| Tool Selection | Not expected | Comfortable asking why a certain tool was selected | Adds input and discusses implications of choices | Responsible for tool selection |
| Data Pipeline Design | Conceptual understanding; raw data must be refined to be useful | Builds pipelines as directed; not expected to design | Designs standard pipelines with oversight from Tier 4 | Designs basic to complex pipelines and defines standards |
Business
| Capability | Tier 1 | Tier 2 | Tier 3 | Tier 4 |
|---|---|---|---|---|
| Identify AI Use Cases | Identify what is and is not an AI solution; pros and cons | Identify what is and is not an AI solution; pros and cons | Identify applications of AI across the organization | Identify creative, less-mainstream ways to introduce AI |
| ROI Analysis | Conversationally competent about the need for ROI analysis | Aware of ROI analysis as a concept; not responsible for execution | Aware of ROI needs and works to complete and communicate them | Owns the ROI analysis and navigates tradeoffs |
| AI Risk Identification | Understands conceptual risks of AI | Understands conceptual and technical implementation risks | Understands conceptual, implementation, and production risks | Deep understanding of risks; skilled at mitigation strategies |
Delivery
| Capability | Tier 1 | Tier 2 | Tier 3 | Tier 4 |
|---|---|---|---|---|
| Technical Instructions | Not applicable | Follow detailed technical instructions to complete tasks | Follow vague technical instructions to complete projects | Write and provide the technical instructions and guidance |
| Project Management | Not expected | Not expected | Familiar with basic project management to support the team | Uses project management to keep projects on track and in scope |
| Project Ownership | Not applicable | Not expected | Expected on small projects | Expected |
| Technical Decision Making | Not applicable | Understands decisions | Contributes to decisions | Owns decisions |
| Team Leadership & Mentorship | Not a practitioner yet | Learns from others | Mentors Tier 2 while learning from Tier 4 | Develops team capabilities, mentors others, sets standards |
Communication
| Capability | Tier 1 | Tier 2 | Tier 3 | Tier 4 |
|---|---|---|---|---|
| Stakeholder Communication | None expected | Shares insights on their tasks when asked | Presents solutions to technical and non-technical stakeholders | Communicates the problem, solution, and risks to any audience |
| Change Management & Adoption | Conversationally competent about the need for change management | Aware of change management as a concept; not responsible | Aware of change management needs and works to mitigate issues | Owns the change-management strategy and its execution |