Kaggle Masterclass - build a Machine Learning Portfolio




Kaggle Masterclass - build a Machine Learning Portfolio

This career-ready Masterclass is designed to help you gain hands-on and in-depth exposure to the domain of Data Science by adopting the learn by doing approach. And the best way to land your dream job is to build a portfolio of projects. And the best platform for a Data Scientist is Kaggle!

Over the years, Kaggle has become the most popular community for Data Scientists. Kaggle not only helps you learn new skills and apply new techniques, but it now plays a crucial role in your career as a Data Professional.

This course will give you in-depth hands-on experience with a variety of projects that include the necessary components to become a proficient data scientist. By completing the projects in this course, you will gain hands-on experience with these components and have a set of projects to reflect what you have learned. These components include the following:

  • Data Analysis and Wrangling using NumPy and Pandas.

  • Exploratory Data Analysis using Matplotlib and Seaborn.

  • Machine Learning using Scikit Learn.

  • Deep Learning using TensorFlow.

  • Time Series Forecasting using Facebook Prophet.

  • Time Series Forecasting using Scikit-Time.

This course primarily focuses on helping you stand out by building a portfolio comprising of a series of Jupyter Notebooks in Python that utilizes Competitions and Public Datasets hosted on the Kaggle platform. You will set up your Kaggle profile that will help you stand out for future employment opportunities.



Become a Kaggle Grandmaster. Build a Portfolio of Machine Learning Projects, and take your Career to the Next Level.

Url: View Details

What you will learn
  • Machine Learning
  • Deep Learning
  • Data Analytics

Rating: 4

Level: Intermediate Level

Duration: 3.5 hours

Instructor: Taimur Zahid


Courses By:   0-9  A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z 

About US

The display of third-party trademarks and trade names on this site does not necessarily indicate any affiliation or endorsement of coursescompany.com.


© 2021 coursescompany.com. All rights reserved.
View Sitemap