Data Science With Python

All about Data Science!

Created by : Rated :4.3 612 views

Last Updated: 2023-03-17 06:03:05 English Course Type: Self Learning

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
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

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 perform 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!

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

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

Section 1 : Overview of Data Science 18 Lectures 01:18:03
Lecture 1 :
Overview of Data Science Preview
Lecture 2 :
Overview of Data Analytics
Lecture 3 :
Demo: Overview of Data Analytics
Lecture 4 :
Statistical Analysis and Business
Lecture 5 :
Demo: Statistical Analysis and Business
Lecture 6 :
Python Environment Setup and Essentials
Lecture 7 :
Mathematical Computing with Python
Lecture 8 :
Demo: Mathematical Computing with Python
Lecture 9 :
Scientific Computing with Python
Lecture 10 :
Demo: Scientific Computing with Python
Lecture 11 :
Data Manipulation with Pandas
Lecture 12 :
Demo: Data Manipulation with Pandas
Lecture 13 :
Machine Learning with Scikit-Learn
Lecture 14 :
Natural Language Procssing with Scikit Learn
Lecture 15 :
Data Visualization in Python using Matplotlib
Lecture 16 :
Web Scraping With BeautifulSoup
Lecture 17 :
Python Integration With Hadoop MapReduce and Spark
Lecture 18 :
Resorces

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Yes absolutely & thats one of the advantage of self-paced courses. You can anytime pause or resume the course & come back & forth from one lecture to another lecture, play the videos mulitple times & so on.
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Most of these courses have general questions & answers already covered within the course lectures. However, if you need any further help from the instructor, you can use the inbuilt Chat with Instructor option to send a message to an instructor & they will reply you within 24 hours. You can ask as many questions as you want.
Do i need a pc to access the course or can i do it on mobile & tablet as well?
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Skillcart is an e-learning company that helps learners upskill in different technology 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.