Machine Learning & Deep Learning in Python & R [FREE]

Free Certification Course Title: Machine Learning & Deep Learning in Python & R

Covers Regression, Decision Trees, SVM, Neural Networks, CNN, Time Series Forecasting, and more using both Python & R

Machine Learning & Deep Learning in Python & R

Requirements:

  • Students will need to install Anaconda software but we have a separate lecture to guide you install the same

What you’ll learn:

  • Learn how to solve real life problem using the Machine learning techniques
  • Machine Learning models such as Linear Regression, Logistic Regression, KNN etc.
  • Advanced Machine Learning models such as Decision trees, XGBoost, Random Forest, SVM etc.
  • Understanding of basics of statistics and concepts of Machine Learning
  • How to do basic statistical operations and run ML models in Python
  • Indepth knowledge of data collection and data preprocessing for Machine Learning problem
  • How to convert business problem into a Machine learning problem

Who this course is for:

  • People pursuing a career in data science
  • Working Professionals beginning their Data journey
  • Statisticians needing more practical experience

What is Machine Learning?

Machine Learning is a field of computer science which gives the computer the ability to learn without being explicitly programmed. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.

Why use Python for Machine Learning?

Understanding Python is one of the valuable skills needed for a career in Machine Learning.

Though it hasn’t always been, Python is the programming language of choice for data science. Here’s a brief history:

In 2016, it overtook R on Kaggle, the premier platform for data science competitions.

In 2017, it overtook R on KDNuggets’s annual poll of data scientists’ most used tools.

In 2018, 66% of data scientists reported using Python daily, making it the number one tool for analytics professionals.

This course includes:

  • 35 hours on-demand video
  • 3 articles
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of completion