Course Outline

 Introduction to Python

  • Variables, Tuples and Lists
  • Loops and control statements
  • Modules and imports

Development Environment Installation

  • Installing python
  • Installing Jupyter
  • Installing python modules using Pip

Vectorizing Data in Numpy

  • Creating Numpy arrays
  • Common operations on matrices
  • Using ufuncs
  • Views and broadcasting on Numpy arrays
  • Optimizing performance by avoiding loops
  • Optimizing performance with cProfile

Data Analysis with Pandas

  • Data cleaning
  • Using vectorized data in pandas
  • Data wrangling
  • Sorting and filtering data
  • Aggregate operations
  • Analyzing time series

Data Visualization

  • Plotting diagrams with matplotlib
  • Using matplotlib from within pandas
  • Creating quality diagrams
  • Visualizing data in Jupyter notebooks
  • Other visualization libraries in Python

Using Sklearn

  • Building Supervised Learning Models
  • Building Classification Models
  • Model Training and Evaluation
  • Plotting results
  • Confusion Matrix calculation and Plotting

Introduction to Deep Learning using Keras and TensorFlow

  • Installing TensorFlow and Keras
  • Introduction to Neural Networks
  • Building and Training ANN
  • Introduction to Convolutional Neural Network
  • Building and Training Image Classifier using CNN
  • Training and Evaluating Deep Learning Models

Requirements

This course is exclusively offered to individuals who attended "Python and Data Visualization" with Ahmed on 11th February 2021

  14 Hours
 

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