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

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

Impress interviewers by showing an understanding of the data science field

Learn how to pre-process data

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

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

Perform linear and logistic regressions in Python

Carry out cluster and factor analysis

Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn

Apply your skills to real-life business cases

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

Unfold the power of deep neural networks

Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance

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