Description

Python for Data Analytics and Machine Learning Bootcamp enables you to take your data science skills into a variety of companies, helping them analyze data and make more informed business decisions. The course covers basic and advanced Python, data exploration, data visualization, descriptive analytics, and predictive analytics techniques with the Python language. You will learn about various Python packages like Numpy, Pandas, Scikit Learn, Seaborn. You will also get a chance to learn how to import and export data in using Python, data structures in Python, various statistical concepts, cluster analysis, Regression and classification. 

Course Objectives

Install Python, Jupyter Notebook and learn about the various Python packages

Gain an in-depth understanding of data structure used in Python and learn to import/export data in Python

Define, understand and use the various functions in Python

Learn to do data visualization using Python packages like matplotlib and seaborn

Gain a basic understanding of various statistical concepts

Understand and use linear regression model, and classification techniques in Machine Learning

Learn and use clustering methods including k-means and hierarchical clustering

Target Audience

This course is meant for all those students and professionals who are interested in using the Python's powerful ecosystem

Basic Understanding

There are no prerequisites

Course Content

No sessions available.

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Simpliv LLC
39658 Mission Boulevard,
Fremont, CA 94539, USA

Python for Data Analytics and Machine Learning Bootcamp

Session 1: Basic and Advanced Python

  1. Introduction to Python

    Various datatypes in Python

    Lists

    Tuples

    Dictionaries

    Sets

  2. Core programming concepts

    While Loops

    For Loops

    If Else statements

  3. Functional Programming using Python

    How to create the functions

    Benefits of using the functions

  4. Text Processing using RE module

    Introduction to String operations and RE Module

  5. Exception Handling in Python

    Understand the exception Handling using Python

    Understand the TRY-EXCEPT-ELSE-FINALLY block

Session 2: Data Manipulation and Analytics using Python

  1. Objects in Python

    Matrix

    Data frames

  2. Visualizations in Python
  3. Packages in Python

    Numpy

    Matplotlib

    Pandas

  4. Matrix operations
  5. Dataframes

    Joins and manipulations in Dataframes

Session 3: Machine Learning

  1. Data Pre-processing

    Missing Data

    Categorical Data

    Feature Scaling

    Data Split (Test and Training Set)

  2. Regression

    Simple Linear Regression

    Multiple Linear Regression

  3. Classification

    Logistic Regression

    K Nearest Neighbours (K-NN)

    Support Vector Machine (SVM)

    Navie Bayes

    Decision Tree Classification

    Random Forest Classification

  4. Clustering

    K Means

    Hierarchical Clustering

  5. Association Rule Mining

    Apriori 

  6. Model selection and Boosting

    K Fold Technique

    Grid Search

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