Artificial Intelligence Course

Embark on an enlightening journey in artificial intelligence (AI) with our comprehensive course. Delve into the forefront of technological innovation as you explore machine learning, deep learning, natural language processing (NLP), computer vision, and robotics. Our hands-on approach ensures you gain practical experience in building AI applications that transform industries. Join us to unlock the potential of AI and shape the future.

|| What will I learn?

  • Understand the basic principles and history of artificial intelligence.
  • Apply search algorithms for problem-solving.
  • Represent knowledge using logical and probabilistic models.
  • Develop and evaluate machine learning models.
  • Implement natural language processing techniques.
  • Understand the principles of robotics and autonomous systems.

|| What will I learn?

  • Understand the basic principles and history of artificial intelligence.
  • Apply search algorithms for problem-solving.
  • Represent knowledge using logical and probabilistic models.
  • Develop and evaluate machine learning models.
  • Implement natural language processing techniques.
  • Understand the principles of robotics and autonomous systems.

|| Requirements

  • Proficiency in a programming language (Python preferred)
  • Basic understanding of algorithms and data structures
  • Familiarity with fundamental concepts in probability, statistics, and linear algebra

|| Requirements

  • Proficiency in a programming language (Python preferred)
  • Basic understanding of algorithms and data structures
  • Familiarity with fundamental concepts in probability, statistics, and linear algebra

    • Natural Language Processing 
    • Part I NLTK
    • What is NLP?
    • Typical NLP Tasks
    • Morphology
    • Sentence Segmentation & Tokenization
    • Pattern Matching with Regular Expression
    • Stemming, Lemmatization
    • Stop Words Removal (English)
    • Corpora/Corpus
    • Context Window – Bigram, Ngram
    • Applications of NLP
    • Introduction to the NLTK Library
    • Processing Raw Text
    • Regular Expression
    • Normalising Text
    • Processing Raw Text – Tokenise Sentences
    • String Processing with Regular Expression, Normalising Text
    • Extracting Features from Text
    • Bag-of-Words(BoW), TF-IDF
    • Similarity score Cosine similarity


    • Computer Vision
    • Image Formation
    • Sampling and Quantisation
    • Image Processing – flipping, cropping, rotating, scaling
    • Image statistics & Histogram
    • Spatial Resolution
    • Gray level/Intensity Resolution
    • Spatial Filtering
    • Convolution
    • Smoothing, Sharpening
    • Color Space Conversion & 
    • Histogram
    • Thresholding for Binarization
    • Morphological Operations
    • Image Gradient
    • Bounding Box
    • Sobel’s Edge Detection Operator
    • Template Matching
    • Image Feature – Keypoint and Descriptor
    • Harris Corner Detector
    • Object Detection with HoG
    • Stream Video Processing with OpenCV

    • Advance NLP
    • "Use Logistic Regression, 
    • Naive Bayes and Word vectors to implement Sentiment Analysis"
    • R-CNN
    • RNN
    • Encoder-Decoder
    • Transformer
    • Reformer
    • Embeddings
    • Information Extraction
    • LSTM
    • Attention
    • Named Entity Recognition
    • Transformers
    • HuggingFace
    • BERT
    • Text Generation
    • Named Entity Recognition
    • GRU
    • Siamese Network in TensorFlow
    • Self Attention Model
    • Advanced Machine Translation of Complete Sentences
    • Text Summarization


    • Prompt Engineering
    • Why Prompt Engineering?
    • ChatGPT
    • Few Standard Definitions:
    • Label, Logic
    • Model Parameters (LLM Parameters)
    • Basic Prompts and Prompt Formatting
    • Elements of a Prompt, Context
    • Task Specification
    • Constraints
    • General Tips for Designing Prompts:
    • Be Specific ,Keep it Concise
    • Be Contextually Aware
    • Test and Iterate
    • Prompt Engineering Use Cases
    • Information Extraction
    • Text Summarization
    • Question Answering
    • Code Generation
    • Text Classification
    • Prompt Engineering Techniques
    • N-shot Prompting
    • Zero-shot Prompting
    • Chain-of-Thought (CoT) Prompting
    • Generated Knowledge Prompting

Get in touch

placement report

|| Frequently asked question

An Artificial Intelligence (AI) Course provides an in-depth understanding of artificial intelligence, covering topics such as machine learning, deep learning, natural language processing, computer vision, robotics, and AI ethics. Participants learn to develop AI-powered applications and systems

This course is suitable for students, professionals, and enthusiasts interested in exploring the field of artificial intelligence. It caters to individuals with varying levels of experience, from beginners with no prior knowledge to experienced practitioners looking to deepen their expertise.

Prerequisites may vary depending on the course level and intensity. However, a basic understanding of programming concepts, familiarity with mathematics (such as linear algebra and calculus), and proficiency in a programming language like Python are often recommended.

Most reputable AI courses offer a certificate of completion, which can enhance your credentials and be added to your resume or LinkedIn profile. It's essential to verify the accreditation and recognition of the issuing institution or organization.

Some courses offer job placement assistance or career services, including resume building, interview preparation, and networking opportunities with industry professionals. However, this varies depending on the course provider and the course's focus.

Yes, many AI courses are available online, offering flexibility in terms of timing and location. Online courses often provide video lectures, interactive exercises, and discussion forums to facilitate learning.

After completing the course, you may continue to have access to course materials, online resources, alumni networks, career services, and professional development opportunities to support your continued learning and career growth.

Related courses

Full Stack Data Science Course
Read more
Data Structures & Algorithms Course
Read more
Data Science using Python Course
Read more
Machine Learning Course
Read more
Deep Learning Course
Read more
Computer Vision Course
Read more
Generative AI Course
Read more
× Popup Image

Our latest blog

Visit our valuable articles to get more information.

Wed, 24 Apr 2024

Top 5 High Income skills to learn in 2024 to make a six – figure salary.

Top 5 High Income skills to learn in 2024 to make a six – figure salary.Seeking to propel your career this year and boost your earning potential? Sta...

Useful links

Categories

IT Infrastructure

Development

Data Science

Work with us

Company

Copyright Baroda Institute of Technology© 2024 | Design and Developed By Bit infotech