280, 8 ( 4.0 )
Java is one of the most dynamic, powerful and popular programming languages used today. This is an object-oriented programming language.
260, 8 ( 4.1 )
Enterprise applications provide the business logic for an enterprise. They are centrally managed and often interact with other enterprise software.
265, 7 ( 4.1 )
The Spring Framework is an application framework and inversion of control container for the Java platform.
270, 5 ( 4.0 )
Hibernate ORM (Hibernate in short) is an object-relational mapping framework for the Java language.
120, 6 ( 3.7 )
JavaServer Pages is a technology that helps software developers create dynamically generated web pages based on HTML, XML, or other document types.
936, 5 ( 3.8 )
An interpreted language, Python has a design philosophy which emphasizes code readability (notably using whitespace indentation to delimit code blocks
220, 5 ( 4.0 )
C is a high-level and general-purpose programming language that is ideal for developing firmware or portable applications.
523, 9 ( 4.6 )
With GoLogica’s course on Dojo you will be an expert in developing android applications using Dojo programming features by working on real time.
235, 1 ( 5.0 )
Learn and skill development on our website. We provide expert-led training in various areas, from tech to business. Improve your knowledge, get practical skills,
453, 1 ( 5.0 )
At GoLogica, we offer comprehensive Data Structure Algorithms Online Training designed to elevate your programming expertise. Our course covers essential data structures, algorithms, and their practic
456, 1 ( 5.0 )
GoLogica offers comprehensive training in Programming Basics and Data Analytics with Python. Learn the essentials of programming and data analytics using Python through interactive exercises.
93, 1 ( 5.0 )
Learn GoLogica's Applied Data Science with Python online course to become good at Python programming, working with data, looking at statistics, using machine learning, and making data visualizations.
95, 1 ( 5.0 )
The Data Science Capstone is like the grand finale of a data science course. In this last part, students use what they have learned to work on real projects. They analyze data, use machine learning.