Machine Learning Certification Course For Beginners | Analytics Vidhya ⭐

In this free machine learning certification course, you will learn Python, the basics of machine learning, how to build machine learning models, and feature engineering techniques to improve the performance of your machine learning models.

What is Machine Learning?

Machine Learning is the science of teaching machines how to learn by themselves. Machine Learning is re-shaping and revolutionizing the world and disrupting industries and job functions globally.

Machine learning is so extensive that you probably use it numerous times a day without even knowing it. From unlocking your mobile phones using your face to giving your attendance using a biometric machine, machine learning is being used in almost every stage.

In this age of machine learning, every aspiring data scientist is expected to upskill themselves in machine learning techniques & tools and apply them in real-world business problems.

What will I learn from this course?

  • Python libraries like Numpy, Pandas, etc. to analyze your data efficiently.
  • Importance of Statistics and Exploratory Data Analysis (EDA) in the data science field.
  • Linear Regression, Logistic Regression, and Decision Trees for building machine learning models.
  • Understand how to solve Classification and Regression problems using machine learning
  • How to evaluate your machine learning models using the right evaluation metrics?
  • Improve and enhance your machine learning model’s accuracy through feature engineering

Prerequisites for the Free Machine Learning Certification Course for Beginners

  • This course requires no prior knowledge about Data Science or any tool.

Machine Learning course syllabus

In this free machine learning course, we will be covering the following topics:

  • Python for Data Science
  • Importance of Statistics and EDA
  • Basics of Machine Learning
  • Evaluation Metrics for Machine Learning models
  • Feature Engineering techniques

ENJOY & HAPPY LEARNING! :heart:

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