Build Practical Data Science Skills
Data science combines programming, statistics, and subject knowledge to investigate questions with data. The work includes collecting and cleaning data, exploring patterns, building models, and explaining results and limitations.
Begin with Python and Data Analysis
The Python for Data Science Bootcamp is a starting point for working with data in Python. Learn to organize an analysis, manipulate data, and create visualizations before moving into more specialized modeling work.
SQL Bootcamp develops a complementary skill: retrieving and combining information from relational databases. Python and SQL are often used together in an analysis workflow.
Progress to Machine Learning
The Python Machine Learning Bootcamp builds on Python knowledge. Check its prerequisites and compare the syllabus with the kinds of models and projects you want to work on.
For a broader sequence, explore the Data Science & AI Certificate, offered through Noble Desktop, NYIM's sister school. The program page provides the current included courses and requirements.
Data Analytics or Data Science?
Data analytics often focuses on understanding business activity and communicating findings through reports, dashboards, and statistical analysis. Data science can also include developing and evaluating predictive models. The fields overlap, and job responsibilities vary. Neither is defined simply by having a larger dataset.
If your immediate goal is business reporting, compare our data analytics classes in Excel, SQL, Power BI, and Tableau.
