This course is intended for students who are familiar with Python and are eager to learn more about using it to data science and machine learning. We've designed this course to help students gain a set of skills that will make them incredibly employable in today's employment environment, where the median starting wage for a data scientist can be over $150,000 dollars.

We'll go through all the information you require to use the whole data science and machine learning software stack used by the biggest corporations in the world. Our graduates have landed jobs at prestigious tech firms including McKinsey, Facebook, Amazon, Google, Apple, Asana, and more!

The following topics are covered in this extensive course, which is created to be comparable to bootcamps, which typically cost thousands of dollars:

NumPy with Python, Deep dive into Pandas for Data Analysis, Full understanding of Matplotlib Programming Library,Deep dive into seaborn for data visualizations.

Machine Learning with SciKit Learn, including: Linear Regression, Regularization, Lasso Regression, Ridge Regression, Elastic Net, K Nearest Neighbors, K Means Clustering, Decision Trees, Random Forests, Natural Language Processing, Support Vector Machines,Hierarchal Clustering,

DBSCAN, PCA, Model Deployment etc

In order to provide you with a clear and systematic approach that will help you understand not just how to utilise data science and machine learning libraries, but also why we use them, we've designed the course utilising our expertise teaching both online and in-person. In this course, the mathematical theory underlying the machine learning algorithms is balanced with applications to real-world cases.

Most other courses don't cover the advanced machine learning algorithms that we do! including cutting-edge regularisation techniques and cutting-edge unsupervised learning techniques, like DBSCAN.

Course Duration:-11h 5m