# Data Sciences With Python

Updated on Sep, 2023

Language - English

30-days Money-Back Guarantee

Training 5 or more people ?

## Course Description

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.

• 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

### Goals

What will you learn in this course:

• 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

### Prerequisites

What are the prerequisites for this course?

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

## Curriculum

Check out the detailed breakdown of what’s inside the course

Overview of Data Science
17 Lectures
• Overview of Data Science 07:04 07:04
• Overview of Data Analytics 06:04 06:04
• Demo: Overview of Data Analytics 46:48 46:48
• Statistical Analysis and Business 11:00 11:00
• Demo: Statistical Analysis and Business 41:48 41:48
• Python Environment Setup and Essentials 02:14 02:14
• Mathematical Computing with Python 12:00 12:00
• Demo: Mathematical Computing with Python 22:15 22:15
• Scientific Computing with Python 09:16 09:16
• Demo: Scientific Computing with Python 18:13 18:13
• Data Manipulation with Pandas 04:23 04:23
• Demo: Data Manipulation with Pandas 26:33 26:33
• Machine Learning with Scikit-Learn 07:44 07:44
• Natural Language Procssing with Scikit Learn 02:51 02:51
• Data Visualization in Python using Matplotlib 04:18 04:18
• Web Scraping With BeautifulSoup 05:31 05:31
• Python Integration With Hadoop MapReduce and Spark 05:31 05:31

## Instructor Details

Skillcart

Skillcart - We provide better e-learning experience.

Skillcart is an e-learning company, that helps learners upskill in different technologies domains with its customized courses, that can be used by both beginners and professionals. Skillcart provides self-paced e-learning videos for all types of technical courses. Skillcart has courses available for Artificial Intelligence, Data Science with Python, Machine Learning, Deep Learning, and many more.

## Course Certificate

User your certification to make a career change or to advance in your current career. Salaries are among the highest in the world.

## Feedbacks

G

Gayathrii M

Concepts are explained nicely