Kaggle Masterclass - build a Machine Learning Portfolio
What you'll learn
- Machine Learning
- Deep Learning
- Data Analytics
- Exploratory Data Analysis
- Data Science
- Intermediate Python Programming Skills.
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.
Who this course is for:
- Beginner Python Developers who want to get into Data Science.
- Data Scientists looking forward to expand their skillset.
- Data Scientists and Aspiring Data Scientists who wish to create a strong portfolio for potential career opportunities.
I am a Machine Learning Engineer, with three years of experience in the field of Data Science and Machine Learning. I am a Former Teaching Assistant for the Deep Learning Master's Degree Course and the Natural Language Processing Course. I have worked on a wide range of projects including, but not limited to, Real-time Vehicle Detection and Tracking, Financial Time-Series Forecasting, and Anomaly Detection in Images.