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All Plans Includes
- Full Access to 16000+ online courses
- Play & Pause Course Viewing
HD Recorded Lectures- Access on Mobile/PC/Tablet
- Quizzes and Real Projects
- Certificate of Completion
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
- 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
Course Overview
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:
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Data Science in detail
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Sectors Using Data Science
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Purpose and Components of Python
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Data Analytics Process
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Exploratory Data Analysis (EDA)
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EDA-Quantitative Technique
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EDA - Graphical Technique
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Data Analytics Conclusion or Predictions
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Data Analytics Communication
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Data Types for Plotting
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Data Types and Plotting
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Introduction to Statistics
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Statistical and Non-statistical Analysis
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Major Categories of Statistics
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Statistical Analysis Considerations
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Population and Sample
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Statistical Analysis Process
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Data Distribution
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Dispersion
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Histogram
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Testing
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Correlation and Inferential Statistics
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Anaconda
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Installation of Anaconda Python Distribution
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Data Types with Python
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Basic Operators and Functions
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Numpy
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Creating and Printing an ndarray
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Class and Attributes of ndarray
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Basic Operations
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Activity-Slice It
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Copy and Views
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Mathematical Functions of Numpy
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Analyzing London Olympics Dataset
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Introduction to SciPy
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SciPy Sub Package - Integration and Optimization
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SciPy sub package
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Calculating Eigenvalues and Eigenvector
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Identifying the SciPy Sub Package
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Solving Linear Algebra problem using SciPy
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Performing CDF and PDF using Scipy
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Introduction to Pandas
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Understanding DataFrame
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View and Select Data
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Missing Values
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Data Operations
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File Read and Write Support
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Pandas SQLOperation
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Analyzing NewYork city fire department Dataset
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Introduction to Machine Learning Approach
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How it Works?
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Supervised Learning Model Considerations
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Supervised Learning Models - Linear Regression
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Supervised Learning Models - Logistic Regression
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Introduction to Unsupervised Learning Models
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Pipeline
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Model Persistence and Evaluation
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Building a model to predict Diabetes
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Introduction to NLP
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Applications of NLP
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NLP Libraries-Scikit
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Extraction Considerations
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Scikit Learn-Model Training and Grid Search
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Sentiment Analysis using NLP
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Introduction to Data Visualization
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Line Properties
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(x,y) Plot and Subplots
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Types of Plots
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Drawing a pair plot using seaborn library
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Web Scraping and Parsing
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Understanding and Searching the Tree
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Navigating options
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Navigating a Tree
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Modifying the Tree
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Parsing and Printing the Document
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Web Scraping of Any Website
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Identifying the reasons why Big Data Solutions are Provided for Python.
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Components of Hadoop Core
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Python Integration with HDFS using Hadoop Streaming
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Python Integration with Spark using PySpark
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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!
Pre-requisites
- No prerequisites are required, as the course covers the concepts from the scratch. However, basic knowledge of Python would help.
Target Audience
- 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
Curriculum 18 Lectures 01:18:03
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Section 1 : Overview of Data Science
- 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
Our learners work at
Frequently Asked Questions
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How do i access the course after purchase?
It's simple. When you sign up, you'll immediately have unlimited viewing of thousands of expert courses, paths to guide your learning, tools to measure your skills and hands-on resources like exercise files. There’s no limit on what you can learn and you can cancel at any time. -
Are these video based online self-learning courses?
Yes. All of the courses comes with online video based lectures created by certified instructors. Instructors have crafted these courses with a blend of high quality interactive videos, lectures, quizzes & real world projects to give you an indepth knowledge about the topic. -
Can i play & pause the course as per my convenience?
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. -
How do i contact the instructor for any doubts or questions?
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. -
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Brilliant question? Isn't it? You can access the courses on any device like PC, Mobile, Tablet & even on a smart tv. For mobile & a tablet you can download the Learnfly android or an iOS app. If mobile app is not available in your country, you can access the course directly by visting our website, its fully mobile friendly. -
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Is there any free trial?
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