Data Science Professional Program

The Data Science Professional Program is a 6-month live online course from ALA Academy, followed by a 6-month internship with ALA Core on real data projects. You will learn to build reproducible data workflows, query data with SQL, apply statistics responsibly, build machine learning models, and deliver dashboards and data apps for real decisions.

Course Structure

- Duration: 6 months / 24 weeks

- Sessions: 72 live online sessions (3 per week, 2 hours each)

- Total hours: 144 contact hours

- Months 1-5: 60 data science sessions

- Month 6: 12 career-readiness sessions (CV, LinkedIn, GitHub portfolio, interviews, graduation presentation)

- Internship: 26 weeks with ALA Core

- Entry level: beginner-friendly, with basic computer literacy required

What You Will Learn

- Python, Jupyter, Git, testing, and reproducible project structure

- NumPy and pandas for data wrangling and data quality

- SQL: joins, aggregations, CTEs, and window functions

- Probability, sampling, hypothesis testing, effect size, and statistical power

- Regression inference, group comparisons, and A/B test design

- Data acquisition from files, databases, and APIs

- Data visualization, storytelling, and business metrics

- Product and customer analytics: funnels, cohorts, and retention

- Time series analysis and forecasting

- Interactive data apps with Streamlit

- Machine learning with scikit-learn: pipelines, regression, classification, tree ensembles, model selection, and clustering

- Interpretability, fairness, and responsible data science

- Data validation, monitoring, and maintenance

Projects and Assessment

- Foundation project: reproducible exploratory data analysis

- Project 1: SQL and statistical analysis for a real decision

- Project 2: Analytical data product with an interactive dashboard

- Project 3: Predictive or segmentation data science solution

- An integrated capstone project with a technical acceptance gate

- Career package and graduation presentation before an ALA Core panel

Career Month

Build a technical CV, a LinkedIn profile, and a curated GitHub portfolio. Complete a technical mock interview covering Python, SQL, statistics, and machine learning, and present your graduation project.

Real-World Internship

Work alongside ALA Core data, software, QA, and product teams on live internal or client projects with approved datasets, real repositories, and stakeholder delivery. You get least-privilege access under an assigned mentor, with no independent production changes.

Who Is This For?

Beginners and career changers who want to become data analysts, data scientists, or junior machine learning practitioners.