Career Course

Advanced Diploma in Software Engineering (ADSE) 

Career Courses
782+
Instructional Hours

Why Choose This AI & ML Course?

Course Overview

Our comprehensive course curriculum covers everything from fundamentals to advanced techniques, preparing you for a successful career.

782
Instructional Hours
0
Comprehensive Modules
0
Lab Hours
0
Capstone Project
Module Duration (Hours) Theory Lab Self-Study Tools/Software
Web Component Development using Jakarta EE 40 20 20 16
Building Java Web Applications with Spring Framework 24 12 12 6
Introduction to Dart Programming 16 8 8 8
Application Development Using Flutter and Dart 40 20 20 16
Agile and DevOps 24 24 - 8
eProject-Cross Platform App Development 2 2 - -
Application Based Programming in Python 36 18 18 10
Inferential Statistical Analysis 16 16 - -
AI Primer 16 16 - 16
AI Applications of NLP 40 20 20 8
AI and ML with Python 40 20 20 12
Applied Machine Learning using Python 40 20 20 12
Deep Learning using Neural Networks 60 30 30 12
Capstone Project-Recommendation Engine and Customer Churn Prediction 40 2 38 -
Total Hours 434 228 206 124

What You Will Learn

  • Develop Web applications suited to any Jakarta EE application server using JSP and Servlet APIs
  • Understand and work with the Spring Framework and Spring Boot
  • Build cross platform apps using Flutter Framework and Dart language
  • Develop Web applications suited to any Jakarta EE application server using JSP and Servlet APIs
  • Implement software development process using Agile methodology
  • Develop a Cross Platform App using Dart and Flutter.
  • Understand the basics of statistical analysis, descriptive statistics, predictive analytics, probability, and Bayes theorem.
  • Gain an understanding of AI.
  • Gain knowledge in NLP and learn the use of AI in NLP.
  •  Use important building blocks of AI & ML with Python, make data modelling decisions, interpret output of the algorithms, and validate results.
  • Master ML concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop AI algorithms.
  • Master deep learning concepts and TensorFlow open-source framework, implement deep learning algorithms, and build ANN.
  • Develop a real-world Capstone project on recommendation engine and perform customer churn prediction.

Your Future as an AI Developer

TERM 3A

  • Jakarta EE  Platform 10
  • Spring 6.x, Spring Boot 3.0.x
  • Flutter SDK 1.22 with Dart 2.10.x
  • Python
  • NLP Tools and Libraries
  • Jupyter Notebook, Google Collab
  • TensorFlow

Industry Recognition

  • AI Developer

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