Professional Data Science
Institution: Tecky Academy
Course type: Bootcamp
- In-class
- Part-time
- 6 weeks
- HK$17,988
Study Method
In-class
Study Mode
Part-time
Duration
6 weeks
Training Fee
HK$17,988
Although data science is a broad subject that spreads over multiple disciplines, in this course, we are focusing on the practical aspects of data science which is particularly important for anyone who is interested to kickstart a data science career.
Students attending this course are going to be able to learn the following:
-Train machine learning model and formulate insight from the result
-Analyze the problem to devise a pragmatic solution
-Extract and Cleanse the source data set from sources
-Visualise the data using third-parties libraries
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
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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
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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
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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
