Get Ready For a Modern Career.

Self-Paced College-Level Courses in SQL, Data Analytics, Python Programming, Linear Algebra for Data Science, and More.

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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.

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
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Advanced SQL
Skills Learned:
  • Conditional expressions
  • SQL errors
  • Text operations
  • Search-and-replace
  • Sets, relations, bags
  • Subqueries
  • Advanced joins
  • Functions
  • Data types
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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
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Computer Programming

Introduction 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
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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
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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
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Applied Python
Skills Learned:
  • Using Linux, Vim and Bash
  • Working remotely via ssh
  • Using Git and Github
  • Writing event-driven programs
  • Writing client-server applications
  • Working with Docker images
  • Creating and using Jupyter notebooks
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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
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