Get Ready For a Modern Career in the Era of Automation and Industry 4.0

No Prior Experience Required

STEM (Science, Technology, Engineering and Mathematics) are the words which drive the future. NCLab courses will help you be in demand.

Industry 4.0 Immersion

Computational Literacy
Skills Learned:
  • Computational thinking
  • Problem solving
  • Algorithmic design
  • Conditional logic
  • Accuracy
  • Attention to detail
  • Perseverance
  • Ability to learn from failure
Read More
Spatial Literacy
Skills Learned:
  • Understand the 3D space
  • Think spatially
  • Solve problems using visual-spatial reasoning
  • Extrude planar shapes to 3D
  • Move and rotate 3D shapes
  • Build 3D models
  • Export models for 3D printing
Read More
Data Literacy
Skills Learned:
  • Types and forms of data
  • Relational and non-relational databases
  • RDBMS and SQL
  • Excel spreadsheets
  • Data analytics and visualization
  • Data mining and governance
  • Data quality and controls
Read More

Data Analytics

SQL Fundamentals
Skills Learned:
  • RDBMS and SQL
  • Write basic queries
  • Order and filter data
  • Combine multiple conditions
  • Group results
  • Use aggregate functions
  • Create and manage tables
  • Insert and delete data
  • Join tables
Read More
Advanced SQL
Skills Learned:
  • Conditional expressions
  • SQL errors
  • Text operations
  • Search-and-replace
  • Sets, relations, bags
  • Subqueries
  • Advanced joins
  • Functions
  • Data types
Read More
Predictive Data Analytics with Python
Skills Learned:
  • Import data from CSV files
  • Work with data frames
  • Clean and manipulate data
  • Visualize and present data
  • Simple linear regression
  • Multiple linear regression
  • Logistic regression
Read More

Computer Programming

Intro to Computer Programming
Skills Learned:
  • Computational thinking
  • Logic and problem solving
  • Algorithms and programs
  • Syntax and code formatting
  • Loops and conditions
  • Variables and functions
  • Recursion
Read More
Python Fundamentals
Skills Learned:
  • Calculations with Python
  • Text string operations
  • Loops and conditions
  • Variables and functions
  • Operations with data files
  • Visualization of data
  • Using Python libraries
  • Principles of software design
Read More
Advanced Python
Skills Learned:
  • Introduction to OOP
  • Advanced concepts of OOP
  • Recursion, binary trees
  • Anonymous lambda functions
  • Iterables, iterators, generators
  • Filters and maps. decorators
  • JSON and XML
  • Basics of working with data
Read More
Applied Python
Skills Learned:
  • Using Linux
  • Using Vim and Bash
  • Working remotely via ssh
  • Using Git and Github
  • Writing large programs
  • Writing event-driven programs
  • Writing client-server applications
  • Ensuring software quality
Read More

Linear Algebra for Data Science

Linear Algebra
Skills Learned:
  • Vector and matrix calculus
  • Systems of linear equations
  • Linear transformations
  • Eigenvectors and eigenvalues
  • Determinants, linear spaces
  • Inner product, norm, orthogonality
  • Matrix factorizations
  • Least-squares problems
  • Singular value decomposition
Read More

Cookie consent

This website or its third party tools use cookies, which are necessary to its functioning and required to achieve the purposes illustrated in the Privacy Policy. If you want to know more or withdraw your consent to all or some of the cookies, please refer to the Privacy Policy. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to the use of cookies.