Example Curriculum
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Introduction Dists Analytics, Types of Analytics, How Data Analyst and Business Analyst Different Scope of Data Analytics and Business Analytics
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Calculation Functions Basic and Advance and Formulas V lookup , H lookup , and Lookup
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Logical functions , text functions , Conditional formating( Basic and Advance )
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Pivot tables in details , Table , slicers , timers, Data analysis in Excel.
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Chars, power query, Stats Introduction
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What is Statistics, Types of Statistics, Descriptive Statistics, Inferential Statistics, Central Tendency, Measure of Central Tendency and Spread
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Types of Errors in Machine Learning Population and Sample Test in Inferential Statistics, P-value Tables and Critical value, Confidence Interval , T-test Significance, alpha Critical value, Degree of freedom.
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Types of Errors in Machine Learning Population and Sample Test in Inferential Statistics P-value Tables and Critical value Confidence Interval T-test
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T-test in detail Chi-square in detail Anova in detail , Chi-square in detail with practical implementation . Anova in detail with practical implementation.
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Introduction to Python , Intro to IDE, how to install anaconda, Julyter etc
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Introduction of python, Statements, Indentations, Comments, Variables , Datatype, Typecasting, Type Conversion, Input and Ouput Statements
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Operators, control flows, built-in data structures.
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Working with Text and All Important Methods of Text. Regular Expressions.
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Working with Text and All Important Methods of Text. Regular Expressions.
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Regular Expression, Function, Arguments, Parameters.
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Function Lambda Function, File handling Exception Handling.
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File handling Pandas Introduction Pandas Import Export
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Data Inspection, Data Cleaning, Data Manipulation
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Numpy Matplotlib,Data Aggregation, Custome Aggregation Join , merge, Concatenate DataFrames
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