About KAI Class

Integrated learning platform for things related to AI

Online/Recorded courses for AI with minimal prerequisites

KAI was started to make AI accessible for everyone and that can be possible by minimizing prerequisites to increase online course success rates. We have courses for things that gives you knowledge to build AI machines, codes, tools etc.

Live Online Courses

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Affordable Recorded Courses

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Anyone can learn

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Our Educator

Kushal Sharma

Founder & Principal Tutor

About Kushal Sharma

  • Former Data Scientist
  • Passive AI Researcher
  • Corporate Trainer
  • Consultancy in AI
  • Educator AI | ML | DS | DL
  • Workshops
  • Research Intern at Axis India Machine Learning Research Labs, Jaipur
  • Skills in applying intricate algorithms based on deep-dive statistical analysis and predictive data modeling that were used to deepen the relationships, strengthen longevity and personalize interactions with customers,
  • Proficiency in analyzing and processing complex data sets using advanced querying, visualization, and analytics tools.
  • Knowledgeable and detail-oriented in utilizing statistical models
  • Broad scientific and mathematical knowledge with the ability to apply learning to real-world situations

Presented a research paper titled “Infant Weeping calls decoder using Statistical Feature Extraction and Gaussian Mixture Models” at “The Tenth International Conference on Computing, Communications, and Networking Technologies“ at IIT Kanpur.

In this research, he tried to decode the baby crying voices which can be so helpful for novice parents if they can get why their baby is crying which can save a lot of money and time that they spent at pediatricians.

Presented a research paper titled “Positive and Negative vibe classifier by converting two-dimensional image space into one-dimensional audio space using statistical techniques for feature extraction and deep learning for classifying” at the “Springer conference“ at NIT Kurukshetra, Haryana, India.

This paper describes how to classify negative and positive vibes in images which is based on converting images to audios. Also, this paper describes what features to extract in doing audio classification of these types of audio signals and classifying them using multilayer perceptron with special weight initialization and hyperparameters

Presented a research paper titled “Identifying Depression in a Person Using Speech Signals by Extracting Energy and Statistical Features” at the “IEEE Conference“ at NIT, Bhopal, Madhya Pradesh.

This paper is about identifying depression status in a human with their speech signals using Deep Learning

Dean at Jaipur School Of AI

This is a non-profit agency run by Mr. Siraj Raval. Kushal Sharma manages the community of AI for the Jaipur region and has conducted many pro bono Classes for young Students

Remote Data Scientist, TVMucho, London, UK
Worked as a remote data scientist for TV Mucho for analyzing data on customer behavior.

  • Well versed with the ML Problems to the most appropriate ML Algorithms according to the task at hand: Prediction, Classification and Clustering
  • Supervised Learning(Classification and Regression) Algorithms and Unsupervised Learning(Clustering and Dimensionality Reduction)
  • Deep Learning CNN, RNN, Feed Forward Neural Networks, Generative Adversarial Networks, Variational Autoencoders, good working knowledge of all the tools involved in making statistical inference
  • Different metrics involved in descriptive Univariate and Multivariate statistics
  • Frequentist Inference(Hypothesis Testing, ANNOVA)
  • Complete Knowledge of Python with Pandas, Numpy, Scikit Learn, Tensorflow, Keras, Scipy, PyTorch and can code all the ML algorithms without any pre-written python module
  • Data Pre-processing and Data Mining
  • Matrix Algebra(Singular and Non-Singular Matrices, Orthogonal Matrices, Inverse of a Matrix, Positive Definite Matrices and Negative Definite Matrices
  • Audio and Image Processing, Feature Extraction, Image/Signal Processing
  • Image Processing basic and advanced algorithms such as SIFT, SURF, Edge Detection, Hough Transformation(Line/Generalized), Dithering, Histogram Equalization

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