Data Science with Python

Languages
English
Duration
44 hours
Investment
$$$$$
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Course Contents

  • ​Career building python course to make you succeed as a Data Scientist
  • With Interactive Python Exercises you will get Hands on experience
  • You will learn different data structures, functions, advance libraries like NUMPY, PANDAS, Matplotlib, SKLEARN, etc.
  • You will e train on different Machine Learning Module

  1. ​Introduction to Data Science
    • Data Science
    • Data Scientists
    • Examples of Data Science
    • Data Science and Big Data
    • Tools for Data Sciences Analysis
    • Summary
  2. Data Analytics Overview
    • Processes in Data Science
    • Exploratory Data Analysis (EDA)
    • Data Visualization
    • Hypothesis Building
    • Hypothesis Testing
    • Summary
    • Quiz
  3. Statistical Concepts & Business Applications
    • Descriptive Statistics
    • Statistical and Non-Statistical Analysis
    • Measures of Central Tendency
    • Knowledge Check
    • Descriptive Statistics
    • Bell Curve
    • Symmetric Distribution
    • Data Distribution
    • Hypothesis Testing
    • Chi-Square Test
    • Correlation Matrix
    • Applications of Inferential Statistics
    • Summary
    • Quiz
  4. Python: Environment Setup and Essentials
    • Python Installation
    • Python for Windows
    • WinPython
    • Anaconda
    • Python Version
    • Demo 1 - Python Installation using Anaconda distribution
    • IPython Notebook
    • The Jupyter Notebook
    • Summary
    • Quiz
    • Summary of day's session
  5. Mathematical Computing with Python (Numpy)
    • NumPy
    • Attributes of ndarray Object
    • Demo 1 - Create arrays in NumPy
    • Demo 2 - Print arrays in NumPy
    • Demo 3 - Basic operations in NumPy
    • Knowledge Check 1
    • Universal Functions (ufunc)
    • Shape Manipulation
    • Copy and Views
    • Knowledge Check 2
    • Broadcasting
    • Knowledge Check 3
    • Demo 4 - Indexing for arrays in NumPy
    • Advanced Indexing
    • Linear Algebra
    • Mini Project 1
    • Mini Project 2
    • Summary
    • Quiz
  6. Scientific computing with Python (Scipy)
    • SciPy and its Characteristics
    • Basics of NumPy
    • SciPy Subpackage
    • SciPy Subpackage—Integration
    • Knowledge Check 2
    • SciPy Subpackage—Optimize
    • Linear Algebra
    • Demo 1 - Calculate Eigenvalues
    • Knowledge Check 1
    • Demo 2 - Descriptive Statistics using SciPy
    • Demo 3 - Solve svd
    • Demo 4 -Calculate Norm
    • SciPy Subpackages—Weave
    • Demo 5 - Calculate File IO Value
    • Mini Project 1
    • Mini Project 2
    • Summary
    • Quiz
  7. Data Manipulation with Python (Pandas)
    • Summary of day's session
    • Introduction to Pandas
    • Data Structures
    • Series
    • Knowledge Check 1
    • DataFrame
    • Data Viewing
    • Demo 1 - How to view the data
    • Knowledge Check 2
    • Data Selection
    • Demo 2 - Select data from data sets Part A
    • Demo 3 - Select data from data sets Part B
    • Panel
    • Missing Data
    • Knowledge Check 3
    • Demo 4 - Manage missing data
    • Operations on Data
    • Mini Project 1
    • Mini Project 2
    • Summary
  8. Machine Learning with Python (Scikit-Learn)
    • Quiz
    • Machine Learning
    • Supervised and Unsupervised Learning
    • Scikit-Learn
    • Knowledge Check 1
    • Estimator Object
    • Knowledge Check 2
    • Regression Problem
    • Demo 2 - Linear Regression
    • Applications of Linear Regression
    • Demo 3 - Logistic regression
    • Clustering
    • Demo 4 - Flat Clustering (K-means algorithm)
    • Knowledge Check 3
    • Dimensionality Reduction
    • Demo 5 - Principal Component Analysis
    • Demo 6 - Independent Component Analysis
    • Demo 7 - Pipelining
    • Demo 8 - Model Persistence
    • Mini Project 1
    • Mini Project 2
    • Summary
    • Quiz
    • Summary of day's session
  9. Natural Language Processing with Python (Scikit-Learn)
    • Natural Language Processing
    • Knowledge Check 1
    • NLP Libraries in Python
    • Scikit-learn Operations
    • Machine Learning on Text Data
    • Mini Project 1
    • Mini Project 2
    • Summary
    • Quiz
  10. Data Visualization in Python with Matplotlib
    • Matplotlib
    • Demo 1 - Plot with matplotlib- Not there.
    •  Line Properties
    • Demo 2 - Create Different Subplots
    • Layout
    • Types of Plots
    • Demo 3 - Create a histograms
    • Demo 4 - Create pie chart
    • Demo 5 - Create an errorbar plot
    • Mini Project 1
    • Mini Project 2
    • Summary
  11. Web Scraping with Python
    • Quiz
    • Web Scraping
    • BeautifulSoup
    • Knowledge Check 1
    • Extracting a Web Page
    • Knowledge Check 2
    • Parse Tree
    • Demo 1 - Navigating the Tree
    • Searching the Tree
    • Knowledge Check 3
    • Parsing a Part of the Document
    • Demo 3 - Parsing Part of the document
    • Mini Project 1
    • Mini Project 2
    • Summary
    • Quiz
    • Summary of day's session

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Instructor Profile

instructor_image

Data Scientist with 10 years of experience executing data-driven solutions to increase efficiency, accuracy, and utility of internal data processing.

This course includes:

  • 100% Online Sessions
  • Instructor led
  • Customizable Syllabus
  • Customizable Schedule
  • Certificate of Completion
  • Training Recordings
  • Training Resources
  • Learner Assessment
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