• Post category:StudyBullet-8
  • Reading time:5 mins read


The main goal of the course is to provide a deeper understanding and hands-on learning experience on the Data Science

What you will learn

This course offers a deep and wide range of skills set from Programming to statistics and machine learning algorithms.

The skills you will attain from this course could make you an expert Data Analyst, Quality Analyst and Business Analyst

The course provides the module of Machine Learning with a prominent SciKit -Learn library.

Algorithms like Regression, Clustering, and Classification are done using the SciKit-Learn library.

Description

This course offers a deep and wide range of skills set from Programming to statistics and machine learning algorithms. The skills you will attain from this course could make you an expert Data Analyst, Quality Analyst and Business Analyst and Statistical Analyst roles.

Machine learning algorithms such as Regression, Clustering, Classification and prominent libraries such as Pandas, Matplotlib, SciKit -learn is covered from this course.

The main goal of the course is to provide a deeper understanding and hands-on learning experience on the Data Science domain with the help of Python programming language along with real-time Data Science projects to provide an overall knowledge on Data Science domain.


Get Instant Notification of New Courses on our Telegram channel.

Noteβž› Make sure your π”ππžπ¦π² cart has only this course you're going to enroll it now, Remove all other courses from the π”ππžπ¦π² cart before Enrolling!


This course covers all the topics from Mathematics to Programming to Visualization techniques that are needed for a Data Scientist role. The whole module that is provided is based on recent trends and growing job opportunities in the Data Science world.

The course provides the module of Machine Learning with a prominent SciKit -Learn library. Algorithms like Regression, Clustering, and Classification are done using the SciKit-Learn library.

  • Pandas library which is used prominently for Data Analysis, Data wrangling and analytics is covered extensively in this course.
  • Data Visualization library Matplotlib is covered from Beginner to Advance level in this course it is very useful for pictorial representation and Data Reporting.
English
language

Content

Machine Learning with Python Course

Introduction to Course
What is Machine Learning
Life Cycle
Introduction to Numpy Library
Creating Arrays from Scratch
Creating Arrays from Scratch Continued
Array Indexing and Slicing
Numpy Array Functions and Shape Modification
Mathematical Operations on Numpy Arrays
Introduction to Pandas Library
Working with Pandas DataFrames
Slicing and Indexing with Pandas
Create DataFrame and Explore Dataset
Data Analysis with Pandas DataFrame
Other Useful Methods in Pandas Library
Introduction to Matplotlib
Customizing Line Plots
Create Plot Using DataFrame
Standard Scaler to Scale the Data
Encoding Categorical Data
Sklearn Pipeline and Column Transformer
Evaluation Metrics in Sklearn
Linear Regression
Evaluation of Linear Regression Model
Polynomial Regression
Polynomial Regression Continued
Sklearn Pipeline Polynomial Regression
Decision Tree Classifier
Decision Tree Evaluation
Random Forest
Support Vector Machines
Kmeans Clustering
KMeans Clustering – Hands On
Data Loading and Analysis
Dimensionality Reduction with PCA
Hyper Parameter Tuning
Summary