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Data Science

Extract insight from data using statistics, visualization, and storytelling.

6 weeksOne day a weekCapstone project

Curriculum

Your six-week path

Each week meets once and builds on the previous session, ending in a hands-on capstone.

  1. 1Week 1

    The Data Science Mindset

    Frame problems and understand the data lifecycle.

    • Roles across the data science lifecycle
    • Asking answerable questions from data
    • Tooling: Python, SQL, and notebooks
    • Ethics and data privacy fundamentals
  2. 2Week 2

    Data Wrangling

    Acquire, clean, and reshape messy datasets.

    • Loading data from files, APIs, and databases
    • Cleaning and transforming with pandas
    • Joining, grouping, and aggregating
    • Handling dates, text, and missing data
  3. 3Week 3

    Exploratory Data Analysis

    Discover patterns and relationships visually.

    • Descriptive statistics and distributions
    • Correlation and covariance
    • Visualization with matplotlib and seaborn
    • Detecting anomalies and data quality issues
  4. 4Week 4

    Statistical Inference

    Draw reliable conclusions from samples.

    • Probability distributions and sampling
    • Hypothesis testing and p-values
    • Confidence intervals
    • A/B testing in practice
  5. 5Week 5

    Predictive Modeling

    Apply models to forecast and classify.

    • Regression and classification refresher
    • Feature engineering for prediction
    • Model evaluation metrics
    • Time-series basics
  6. 6Week 6

    Communicating Insight & Capstone

    Turn analysis into decisions with dashboards.

    • Data storytelling principles
    • Building interactive dashboards
    • Presenting to non-technical stakeholders
    • Capstone: full analysis and presentation

Levels

Choose the level that fits you

Data Science is offered at five levels. Sign up for the one that matches your current experience.

  1. 1

    Beginner

    Start from the fundamentals

    For students who are new to the subject. Covers core concepts, key terms, and the basics you need to get started with confidence.

  2. 2

    Intermediate

    Build on what you know

    For students with some prior knowledge. Goes deeper into practical skills, tools, and real-world application of the fundamentals.

  3. 3

    Advanced

    Master complex skills

    For experienced students ready for challenging material, advanced techniques, and independent problem-solving.

  4. 4

    Professional

    Industry-ready expertise

    For working professionals. Focuses on workplace scenarios, best practices, and the standards expected in the field.

  5. 5

    Diploma

    Full certification track

    A comprehensive track combining all levels toward a Fisko Foundation diploma, with a final assessment and certificate of completion.

Test your knowledge

A quick 4-question check on Data Science. Pick an answer for each question, then submit to see your score.

  1. 1. What does EDA stand for?

  2. 2. Which tool is commonly used to query relational databases?

  3. 3. A p-value helps you decide whether to:

  4. 4. Which library is widely used for data wrangling in Python?

0 of 4 answered

Ready to enroll in Data Science?

Secure your place in the next six-week cohort and start building practical skills one day a week.

Enroll now

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