Project SPARTA scholars can take courses on various fields of Data Science and Analytics through learning pathways. Below are the six (6) learning pathways available in the program:
SPARTA scholars may only take one (1) learning pathway at a time. Upon completion, scholars may again choose another pathway to take.
1. Data Associate (click the link to view the core courses for this pathway)
- Data associate sources, processes, analyzes data and provide reports to explain insights. Data associates develop and prepare repeatable reporting that highlights relevant trends and other significant results they deduce. They may also provide some basic commentaries on observable trends and patterns, that may help senior analysts and managers easily identify opportunities for follow-up in-depth analysis for actionable insights. No prior work experience or domain knowledge is required of data associates.
- In this pathway, you will be trained across the following competencies:
- Operational Analytics
- Data Visualization
- Data Governance
- Computing
2. Data Steward (click the link to view the core courses for this pathway)
- Data steward is the gatekeeper of data. Data stewards are responsible for ensuring that an organization’s data is well-defined, managed, and ready to use for downstream reporting, analytics, modeling, or even artificial intelligence (AI) use cases. They are also in-charge of overall data governance, with the major task of working across the organization to control and improve data quality, oversee data technology and infrastructure, and ensure data acquisition, usage, maintenance, access, and security comply with policies, rules, regulations, and ethical practice.
- In this pathway, you will be trained across the following competencies:
- Data Governance
- Operational Analytics
- Domain Knowledge
- Data Visualization
- Research Methods
- Computing
3. Data Engineer (click the link to view the core courses for this pathway)
- Data engineer builds and manages data workflows, pipelines, ETL processes, and platforms. Data engineers are mainly responsible for management of the entire data lifecycle: ingestion, processing, surfacing, and storage. They leverage their in-depth knowledge of programming, databases, data warehousing, ETL, and data architecture and pipelining, to use complex tools and techniques to handle data at scale. They also deploy machine learning and statistical models in production. This requires data engineers to understand analytics and business intelligence, together with various frameworks and technologies.
- In this pathway, you will be trained across the following competencies:
- Data Engineering
- Operational Analytics
- Data Governance
- Computing
- Data Visualization
- Data Analytics Methods and Algorithms
- Statistical Techniques
- Research Methods
- Domain Knowledge
4. Data Scientist (click the link to view the core courses for this pathway)
- Data scientist is a specialist who applies their expertise in statistics and building machine learning models, enriched with programming, to make predictions and answer key business questions. Data scientists tackle more open-ended questions, leveraging their knowledge of advanced statistics and algorithms. They bring new approach and perspective to data, raising new questions and creating sophisticated analytical models to derive new insights from data. They also exhibit business acumen and domain knowledge in order to provide in-depth analysis, to derive accurate predictions, to recommend actionable insights, and to present insights in a way that is understandable by business stakeholders.
- In this pathway, you will be trained across the following competencies:
- Statistical Techniques
- Data Analytics Methods and Algorithms
- Computing
- Operational Analytics
- Research Methods
- Domain Knowledge
- Data Governance
- Data Visualization
- Data Engineering
5. Data Analyst (click the link to view the core courses for this pathway)
- Data analyst leverages reporting, data analysis, and modelling techniques to solve problems and gather insight across functional domains. Data analysts are concerned with business implications of data and actions that should result from them. They analyze data and assess requirements from a business perspective related to an organization’s overall system. They also summarize facts and creates a story out of data, upon which these facts and stories become input for decision-making or a flag for a deep-dive analysis or statistical follow-up. They require prior work experience or domain expertise to become a link between IT, data specialists, and the business stakeholders.
- In this pathway, you will be trained across the following competencies:
- Domain Knowledge
- Operational Analytics
- Data Visualization
- Data Governance
- Research Methods
- Computing
6. Analytics Manager (click the link to view the core courses for this pathway)
- Analytics manager oversees analytical operations and communicate insights to executives. Analytics managers translate analytical results to actionable business items. Their role is to drive business outcomes, bridging technical expertise from steward, engineer, scientist and analyst with the operational expertise of the business functions. They can be individuals who manage a team of data science and analytics specialists, or functional managers or leaders who make data-driven decisions.
- In this pathway, you will be trained across the following competencies:
- Domain Knowledge
- Operational Analytics
- Data Visualization
- Data Governance
- Research Methods
- Data Engineering
- Statistical Techniques
- Data Analytics Methods and Algorithms
- Computing