Python Programming


Python Programming

Python is a high-level, interpreted, interactive and object-oriented scripting language. Python is designed to be highly readable. It uses English keywords frequently where as other languages use punctuation, and it has fewer syntactical constructions than other languages.• Python is Interpreted − Python is processed at runtime by the interpreter. You do not need to compile your program before executing it. This is similar to PERL and PHP.• Python is Interactive − You can actually sit at a Python prompt and interact with the interpreter directly to write your programs.• Python is Object-Oriented − Python supports Object-Oriented style or technique of programming that encapsulates code within objects.• Python is a Beginner’s Language − Python is a great language for the beginner-level programmers and supports the development of a wide range of applications from simple text processing to WWW browsers to games. 

Target Audience

The Python Programming Certification Course is a good fit for the below professionals:Programmers, Developers, Technical Leads, Architects, FreshersData Scientists, Data AnalystsStatisticians and AnalystsBusiness AnalystsProject ManagersBusiness Intelligence Managers

Course Objectives

After completing this course, you will be able to:Write python scripts, unit test codeProgrammatically download and analyse dataLearn techniques to deal with different types of data – ordinal, categorical, encodingLearn data visualizationUsing IPython notebooks, master the art of presenting step by step data analysis  

Course Curriculum

Section 1 : Introduction to Python
Overview of PythonThe Companies using PythonOther applications in which Python is usedDiscuss Python Scripts on UNIX/WindowsValues, Types, VariablesOperands and ExpressionsConditional StatementsCommand Line ArgumentsWriting to the screen
Section 2: Sequences and File Operations
Python files I/O FunctionsNumbersStrings and related operationsTuples and related operationsLists and related operationsDictionaries and related operationsSets and related operations
Section 3 : Deep Dive – Functions, OOPs, Modules, Errors and Exceptions
FunctionsFunction ParametersGlobal variablesVariable scope and Returning ValuesLambda FunctionsObject Oriented ConceptsStandard LibrariesModules Used in PythonThe Import statementsModule search pathPackage installation waysErrors and Exception HandlingHandling multiple exceptions
Section 4 : Introduction to NumPy & Pandas
NumPy – arraysOperations on arraysIndexing slicing and iteratingReading and writing arrays on filesPandas – data structures & index operationsReading and Writing data from Excel/CSV formats into Pandas
Section 5 : Data Visualisation
matplotlib libraryGrids, axes, plotsMarkers, colours, fonts and stylingTypes of plots – bar graphs, pie charts, histogramsContour plots
Section 6 : Data Manipulation
Basic Functionalities of a data objectMerging of Data objectsConcatenation of data objectsTypes of Joins on data objectsExploring a DatasetAnalyzing a dataset
Section 7 : Developing Web Maps and Representing information using Plots
Use of Folium LibraryUse of Pandas LibraryFlow chart of Web Map applicationDeveloping Web Map using Folium and PandasReading information from Dataset and represent it using Plots
Section 8 : Computer vision using OpenCV and Visualisation using Bokeh
Beautiful Soup LibraryScrap all hyperlinks from a webpage, using Beautiful Soup & RequestsPlotting charts using BokehPlotting scatterplots using BokehImage Editing using OpenCVFace detection using OpenCVMotion Detection and Capturing Video