Artificial Intelligence Syllabus

Get in-depth knowledge of MACHINE LEARNING and DEEP LEARNING models as well as learn to deploy them on the web.

Python

  • 1. Basic python
  • 2. File handling in python
  • 3. Database connection
  • 4. OOP's programming
  • 5. Libraries (Tensorflow, pandas, bumpy)
  • 6. Django framework for the deployment of machine learning models

Machine learning

  • 1. Linear regression
  • 2. Logistic regression
  • 3. Support vector machines
  • 4. Decision trees
  • 5. Random forest
  • 6. Gradient boosting

Deep learning

  • 1. Perceptron
  • 2. Perceptron learning algorithm
  • 3. Gradient descent
  • 4. Backpropagation
  • 5. Feed forward neural networks
  • 6. Convolution neural networks
  • 7. Recurrent neural networks (LSTM and GRU)
  • 8. Generative adversarial networks

Career Opportunities

Around 27% of students Started their careers in AI after completion of the Artificial Intelligence course.

Around 15% of people experience pay increases or promotions.

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