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Part-time

Professional Data Science

Curriculum

Turn Data into Treasure

Python Programming

Python Programming

Python is the most popular programming language for data science nowadays because of its widely supported data science and machine learning libraries. It is thus important to understand the in and out of Python before diving deep into the ocean of data science.

It covers in-depth knowledge of the following:

  • Python
  • Jupyter Notebook
Python
Jupyter Notebook
Data Science Libraries

Data Science Libraries

There are lots of libraries in existence to make working with data science an easier job. With the help of these libraries, data scientists can extract, cleanse and visualise the datasets in hand.

Making good use of the data science libraries paves a good foundation for further advancement in your career.

This course covers the in-depth knowledge of the following:

  • Numpy
  • Pandas
  • Seaborn
  • Matplotlib
Matplotlib
numpy
scipy
Machine Learning Libraries

Machine Learning Libraries

It is part of the daily routines for data scientists to make use of machine learning libraries. With the usage of these libraries, data scientists can effectively discover the insights behind the enormous amount of collected data, which can further help them to advise on crucial decision-making in businesses.

This course covers the in-depth knowledge of the following:

  • Scikit-learn
  • K-means Clustering
  • Decision Tree
Scikit-learn
Decision Tree
Deep Learning Libraries

Deep Learning Libraries

Deep learning is a major branch of the boarder field of machine learning. It undergoes tremendous development in multiple fields in recent years. Facial recognitions, Languages synthesis, Reinforcement Learning are some of the prominent examples.

This course covers the in-depth knowledge of the following:

  • Neural network
  • Tensorflow
  • Keras
Tensorflow
Keras
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