What you'll get

  • Job Credibility
  • Certification Valid for Life
  • Live Classes
  • Certificate of Completion

Exam details

  • Mode of Exam : Online
  • Duration : 1 Hour
  • Multiple Choice Questions are asked
  • No. of Questions are asked : 50
  • Passing Marks : 25 (50%)
  • There is no negative marking

The course Certificate in Python Machine Learning is designed to make students understand the industry needed concepts of machine learning to become a skilled data scientist. This online course is a course of 6 months duration, divided into small modules to make a better experience. So, This makes it the best python course for you.

What will you learn if you enrol for this online python certification?

You will get python online tutorial and after completion of this course you will be able to:

  • Building Good Training Datasets,
  • Data Preprocessing, Compressing Data,
  • Using scikit-learn,
  • Model Evaluation and Hyperparameter Tuning,
  • Combining Different Models for Ensemble Learning,

Further, you can check the syllabus of the course. 

Why should you learn a python programming language?

Python is a high-level programming language. Which runs on the cloud and this software used by many companies for data science, machine learning, algorithms, data mining. It’s popularity increasing every day because of its features and versatility. Here are the few of these companies are using python such as Google, Facebook, Instagram, etc.

What are the essential requirements for this python certification course?

You do not need any prior experience. As this Python online course is designed in such a way that anyone can understand the intermediate or beginner level.

Course Content

Total: 38 lectures
  • What Is Machine Learning?
  • Getting the Tools
  • What Is NumPy?
  • Creating NumPy Arrays
  • Array Indexing
  • Reshaping Arrays
  • Array Math
  • Array Assignment
  • What Is Pandas?
  • Pandas Series
  • Pandas DataFrame
  • What Is matplotlib?
  • Plotting Line Charts
  • Plotting Bar Charts
  • Plotting Pie Charts
  • Plotting Scatter Plots
  • Plotting Using Seaborn
  • Introduction to Scikit‐learn
  • Getting Datasets
  • Getting Started with Scikit‐learn
  • Data Cleansing
  • Types of Linear Regression
  • Linear Regression
  • Polynomial Regression
  • What Is Logistic Regression?
  • Using the Breast Cancer Wisconsin (Diagnostic) Data Set
  • What Is a Support Vector Machine?
  • Kernel Trick
  • Types of Kernels
  • Using SVM for Real‐Life Problems
  • What Is K‐Nearest Neighbors?
  • What Is Unsupervised Learning?
  • Using K‐Means to Solve Real‐Life Problems
  • What Is Microsoft Azure Machine Learning Studio?
  • Deploying ML
  • Case Study
  • Deploying the Model
  • Creating the Client Application to Use the Model

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