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Artificial Intelligence


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Slide One

Artificial Intelligence


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Dive into the world of Artificial Intelligence with our comprehensive course. Explore key concepts like machine learning, neural networks, and natural language processing. Gainon experience through practical projects, preparing you for success in this rapidly advancing field.

Course Fee: Enquire Now
Eligibility: Graduate / Under Graduate
Admission Helpline: +91 9321317700

Course Features

Free Books & Materials

Authorized Certification

Extra Hour for Practice

Course Tracking System

Flexible Batch Timings

Student Development

A.C. Lab

After Course Support

Campus Interviews

Job Assistance

Course Details

Artificial Intelligence Course Overview

  • Introduction to AI:
    – Overview of AI and its applications.

  • Convolutional Neural Networks (CNN):
    – Basics of CNN.
    – Building CNN Architecture.
    – Importance of CNN in Image Classification.

  • Transfer Learning:
    – VGG16, VGG19, ResNet50, InceptionV3.
    – Leveraging pre-trained models.

  • Neural Networks:
    – Understanding neurons.
    – Architecture of Artificial Neural Networks (ANN).
    – Activation functions and optimization.

Natural Language Processing (NLP) Module

  • Introduction to NLP:
    – Basics of Natural Language Processing.
    – Overview of NLP models.

  • Artificial Neural Networks (ANN) in NLP:
    – ANN architecture.
    – Activation functions for NLP.

  • NLP Techniques:
    – NLTK for stemming, lemmatization, regex, and stop words.
    – Corpus analysis, unigram, bigram, trigram.

  • Text Representation:
    – Bag of Words (Count Vectorization).
    – TF-IDF (Term Frequency Inverse Document Frequency).
    – Word Embedding techniques (GloVe, Word2Vec, FastText).

  • Optimization and Regularization:
    – Gradient Descent.
    – Cost functions and regularization.

Practical Applications

  • Image Classification with CNN:
    – Key concepts in CNN for image processing.
    – FastText for text classification.

  • Hands-on Projects:
    – Building simple ANN and CNN models.
    – Implementing word embeddings (GloVe, Word2Vec).
    – Using TextBlob for NLP applications.

  • Course Benefits:
    – Comprehensive understanding of AI, CNN, NLP, and ANN.
    – Practical experience with real-world projects.
    – In-depth knowledge of various pre-trained models.

Enroll Now for a Future in Artificial Intelligence!

Exit Profile

Upon completion of our Artificial Intelligence course, you'll possess a robust skill set ready for various roles in the tech industry. Your exit profile will showcase expertise in machine learning, neural networks, and natural language processing, alongside practical project experience.

  • AI Engineer
  • Data Scientist
  • Machine Learning Engineer
  • Robotics Engineer
  • Natural Language Processing Engineer
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