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Data Science With Python (2022)

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Published 09/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 17 lectures (3h 53m) | Size: 1.32 GB

All about Data Science!

What you’ll learn
Explain Data Science in detail
Explain Data Analytics in detail
Understand the Statistical Analysis and Business
Understand the Python Environment Setup and Essentials
Describe Mathematical Computing with Python
Describe Scientific Computing with Python
Work on Data Manipulation with Pandas
Work on Machine Learning with Scikit-Learn
Understand the working of Natural Language Processing with Scikit Learn
Perform Data Visualization in Python using Matplotlib
Perform Web Scraping with BeautifulSoup
Understand the Python Integration with Hadoop MapReduce and Spark

Requirements
No prerequisites are required, as the course covers the concepts from the scratch. However, basic knowledge of Python would help.

Description
About the Course

The “Data Science” course is an intermediate level course, curated exclusively for both beginners and professionals.

The course covers the basics as well as the advanced level concepts. The course contains content based videos along with practical demonstrations, that performs and explains each step required to complete the task.

Learning Objectives

By the end of the course, you will be able to learn about

Data Science in detail

Sectors Using Data Science

Purpose and Components of Python

Data Analytics Process

Exploratory Data Analysis (EDA)

EDA-Quantitative Technique

EDA – Graphical Technique

Data Analytics Conclusion or Predictions

Data Analytics Communication

Data Types for Plotting

Data Types and Plotting

Introduction to Statistics

Statistical and Non-statistical Analysis

Major Categories of Statistics

Statistical Analysis Considerations

Population and Sample

Statistical Analysis Process

Data Distribution

Dispersion

Histogram

Testing

Correlation and Inferential Statistics

Anaconda

Installation of Anaconda Python Distribution

Data Types with Python

Basic Operators and Functions

Numpy

Creating and Printing an ndarray

Class and Attributes of ndarray

Basic Operations

Activity-Slice It

Copy and Views

Mathematical Functions of Numpy

Analyzing London Olympics Dataset

Introduction to SciPy

SciPy Sub Package – Integration and Optimization

SciPy sub package

Calculating Eigenvalues and Eigenvector

Identifying the SciPy Sub Package

Solving Linear Algebra problem using SciPy

Performing CDF and PDF using Scipy

Introduction to Pandas

Understanding DataFrame

View and Select Data

Missing Values

Data Operations

File Read and Write Support

Pandas SQLOperation

Analyzing NewYork city fire department Dataset

Introduction to Machine Learning Approach

How it Works?

Supervised Learning Model Considerations

Supervised Learning Models – Linear Regression

Supervised Learning Models – Logistic Regression

Introduction to Unsupervised Learning Models

Pipeline

Model Persistence and Evaluation

Building a model to predict Diabetes

Introduction to NLP

Applications of NLP

NLP Libraries-Scikit

Extraction Considerations

Scikit Learn-Model Training and Grid Search

Sentiment Analysis using NLP

Introduction to Data Visualization

Line Properties

(x,y) Plot and Subplots

Types of Plots

Drawing a pair plot using seaborn library

Web Scraping and Parsing

Understanding and Searching the Tree

Navigating options

Navigating a Tree

Modifying the Tree

Parsing and Printing the Document

Web Scraping of Any Website

Identifying the reasons why Big Data Solutions are Provided for Python.

Components of Hadoop Core

Python Integration with HDFS using Hadoop Streaming

Python Integration with Spark using PySpark

Using PySpark to Determine Word Count

…and much more!

If you’re new to this technology, don’t worry – the course covers the topics from the basics. If you’ve done some programming before, you should pick it up quickly.

If you’re a programmer looking to switch into an exciting new career track, this course will teach you the basic techniques used by real-world industry Data Scientist. These are topics any successful technologist absolutely needs to know about, so what are you waiting for? Enroll now!

Who this course is for
Beginner Python developers willing to learn Data Science
Candidates willing to make a career in Data Science
IT professionals willing to upskill their knowledge in Data Science
Freshers/ Beginners who starting their career in this field


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