Python Base and Advanced Programming - Dvanalytics
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Python Base and Advanced Programming

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    Python is a high-level programming language and it is mainly used in the field of mathematics and complex program designing, web development, software development and system scripting. However we will learn Python program uses for data analytics here

    Course Curriculum

    Session - 1
    Python Overview and Installation steps 00:00:00
    Introduction to Python Editors & IDE’s (Canopy, Pycharm, Jupyter, Rodeo, Ipython etc…) 00:00:00
    Work around Jupiter Notebook and its customized settings 00:00:00
    Importing Packages (NumPy, SciPy, scikit-learn, Pandas, Matplotlib, etc) 00:00:00
    Installing & loading Packages & Name Spaces 00:00:00
    Data Types & Data objects/structures 00:00:00
    • Srtings
    • Tuples
    • List
    • Dictionaries
    Variable Types and Values 00:00:00
    Reading and writing data (Importing and Exporting) 00:00:00
    • Importing Data from various sources (Csv, txt, excel, access etc)
    • Database Input (Connecting to database)
    • Viewing Data objects - subsetting, methods
    • Exporting Data to various formats
    • Important python modules: Pandas, beautifulsoup
    Session - 2
    Data Manipulation Steps 00:00:00
    • Sorting/ Filtering
    • Duplicate data handling
    • Smapling/Subsetring
    • Dericed Variable
    • Data type conversion
    • Renaming
    • Formatting
    Session - 3
    Vertical Join- Appending 00:00:00
    Horizontal Join- Merging 00:00:00
      • Inner Join
      • Outer Join
          • Full outer join
            • Un-matched join
          • Left outer join
            • Left null join
          • Right outer join
            • Right null join
      • Keys and Relationships
    Session - 4
    Control flow & conditional statements 00:00:00
    • If-Else
    • Loops (For and While)
    Python Functions 00:00:00
    • Built-in
      • Text, Numeric, Date, Utility
    • User defined function
    Session - 5
    Data Analysis and Visualization steps 00:00:00
      • Creating graphs
        • Bar Chart
        • Pie Chart
        • Line Chart
        • Histogram
        • Boxplot
        • Scatter
        • Density
      • Introduction to model building steps
      • Data exploration and validation
      • Descriptive statistics, Frequency Tables and summarization
      • Univariate Analysis (Distribution of data & Graphical analysis)
      • Bivariate Analysis (Cross Tabs, Distributions & Relationships, Graphical analysis)