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Career Paths

Choose your career. We'll map the route.

Explore what each role really involves — responsibilities, skills, tools, where it is found and how it grows — then follow a clear learning roadmap to get there.

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Career profile

Data Analyst

Turn raw business data into clear answers and decisions.

Data Analytics + GenAI + Agentic AI program Apply now

Typical career progression

  1. 1Junior Data Analyst
  2. 2Data Analyst
  3. 3Senior Data Analyst
  4. 4Analytics Lead / Manager

Titles and timelines vary by company, location and individual experience.

What a Data Analyst does

Data Analysts collect, clean and analyse data to answer business questions. They build reports and dashboards, track KPIs and explain what the numbers mean so teams can act on them.

Day-to-day responsibilities

  1. 01Gather and clean data from spreadsheets, databases and business systems
  2. 02Write SQL queries to extract and aggregate the data a team needs
  3. 03Build and maintain dashboards and recurring reports
  4. 04Track KPIs and flag unusual trends early
  5. 05Run ad-hoc analysis to answer stakeholder questions
  6. 06Present findings clearly with charts and short narratives

Learning roadmap

  1. Stage 1

    Excel

    • Formulas
    • Pivot tables
    • Charts

  2. Stage 2

    SQL

    • Joins
    • Aggregations
    • Window functions

  3. Stage 3

    Python

    • Pandas
    • EDA
    • Visualization

  4. Stage 4

    Power BI

    • Dashboards
    • DAX
    • Data modelling

  5. Stage 5

    Business Insights

    • KPIs
    • Storytelling
    • Reporting

Compare roles

All career paths at a glance.

Find the role that fits your interests, then start with the matching program.

RoleFocusCore toolsLearning pathProgram
Turn raw business data into clear answers and decisions.Excel, SQL, Python, PandasExcel → SQL → Python → Power BI → Business InsightsData Analytics + GenAI + Agentic AI
Use statistics and machine learning to predict what happens next.Python, Jupyter, NumPy, PandasPython → Statistics → Machine Learning → Deep Learning → AIData Science + GenAI + Agentic AI
Build, ship and run machine learning systems in production.Python, PyTorch, Scikit-learn, FastAPIML → Deep Learning → Deployment → ProductionData Science + GenAI + Agentic AI
Build applications powered by large language models.Python, OpenAI / LLM APIs, LangChain, LlamaIndexLLMs → Prompt Engineering → RAG → AI ApplicationsGenerative AI + Agentic AI
Design AI agents that plan, use tools and complete tasks.Python, LangGraph, CrewAI, OpenAI / LLM APIsAgents → Tools → Workflows → Multi-Agent SystemsAgentic AI

Not sure which career fits you?

Talk to an advisor about your background and goals. We will help you pick a role and the right program to start with.

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