The course provides the entire toolbox you need to become a data scientist

Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)

Perform linear and logistic regressions in Python

Be able to create Machine Learning algorithms in Python

using NumPy

statsmodels and scikit-learn

Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data

Improve Machine Learning algorithms by studying underfitting

overfitting

training

validation

n-fold cross validation

testing

and how hyperparameters could improve performance

Fill up your resume with in demand data science skills: Statistical analysis

Python programming with NumPy

pandas

matplotlib

and Seaborn

Advanced statistical analysis

Tableau

Machine Learning with stats models and scikit-learn

Deep learning with TensorFlow

Learn how to pre-process data

Start coding in Python and learn how to use it for statistical analysis

Carry out cluster and factor analysis

Apply your skills to real-life business cases

Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations