WSQ Data Science Bootcamp (Synchronous E-learning)

About This Course

Upon completion of the course, learners will be able to:

Describe data science and its life cycle, Python as a programming language and how to operate it on editor such as Jupyter Notebook

Utilize Python to perform arithmetic, relation and logical operators with different data types and functions

Utilize different methods of data slicing and manipulation on textual data, iterations for repetitive tasks and user defined functions for control and logic flow

Interpret Numpy arrays and use Numpy statistical module in Python for data indexing and iterations

Perform essential operations of Pandas module to extract and manipulate data to prepare for statistical process and machine learning

Build visualizations and graphs using Matplotlib and Seaborn to interpret data and gather insights to support business decisions

Use advanced techniques to clean data to conduct exploratory analysis for better understanding of the data

Apply linear regression machine learning model to predict results of a continuous data type and evaluate its model performance

Use advanced techniques in standardization and normalisation of the datasets to obtain better performance in machine learning models

Apply different algorithms to predict binary or multiclass outcomes and evaluate the model performances among the algorithms

Create and automate hypertuning of machine learning models to obtain optimal machine learning parameters for good machine learning results