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Course Details

Blended
Machine Learning Blended
Last Update:

July 18, 2023

Review:
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About Course

Starting Point For Your Career Path…
Our Mission
& Vision

We help undergrad and post grad students struggling to get industrial
experience with our Industry Grade Mentorship programs which help them
to become corporate-ready individuals and possess the skillset to take on
any challenges without any self-doubt.
Mission
Our aim is to become one of the most preferred
education technology platforms across the globe.
Vision
We envision a world in which each students receives the
effective, equitable, and engaging education they need to
reach their full and unique potential

What Will You Learn?

  • You will learn how to use data science and machine learning with Python.
  • You will create data pipeline workflows to analyze, visualize, and gain insights from data.
  • You will build a portfolio of data science projects with real world data.
  • You will be able to analyze your own data sets and gain insights through data science.
  • Master critical data science skills.
  • Understand Machine Learning from top to bottom.
  • Replicate real-world situations and data reports.
  • Learn NumPy for numerical processing with Python.
  • Conduct feature engineering on real world case studies.
  • Learn Pandas for data manipulation with Python.
  • Create supervised machine learning algorithms to predict classes.
  • Learn Matplotlib to create fully customized data visualizations with Python.
  • Create regression machine learning algorithms for predicting continuous values.
  • Learn Seaborn to create beautiful statistical plots with Python.
  • Construct a modern portfolio of data science and machine learning resume projects.
  • Learn how to use Scikit-learn to apply powerful machine learning algorithms.
  • Get set-up quickly with the Anaconda data science stack environment.
  • Learn best practices for real-world data sets.
  • Understand the full product workflow for the machine learning lifecycle.
  • Explore how to deploy your machine learning models as interactive APIs.

Course Content

Induction Class

Introduction & Installation Python

Programming Elements

Conditions & Loops

Data Structures

Functions & Expection Handling

Add on Topics

Machine Learning

Linear Regression

Logistic Regression

Evaluation Metrices

KNN & SVM

Decision Tree & Ensemble Learning

Problem Statements

Unsupervised Learning-1

Unsupervised Learning-2

Add-on-Topics

Support

4,999.00 7,500.00
  • Instructor
    Elenxia Learning Platform
  • Language
    English

Payment :

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Material Includes

  • 25 hours on-demand video
  • live doubt session per week.
  • 1 article
  • 1 downloadable resource
  • Access on mobile and TV
  • Certificate of completion
  • Internship 100 percent
  • Internship Completion Certificate

Requirements

  • Basic Python Knowledge (capable of functions)

Audience

  • programming,
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