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Python Objects, Numbers & Booleans, Strings, Container objects, Mutability of objects Concept of Packages/Libraries – Important packages (Pandas, NumPy, SciPy, Scikit-learn, Seaborn, Matplotlib)
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Operators – Arithmetic, Bitwise, Comparison and Assignment Operators
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Conditions
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Loops
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Break and Continue Statement
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Range Functions
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Introduction exploratory data analysis
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Descriptive statistics, Frequency Tables and summarization
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Univariate Analysis (Distribution of data & Graphical Analysis)
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Bivariate Analysis (Cross Tabs, Distributions & Relationships, Graphical Analysis)
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Creating Graphs- Bar/pie/line chart/histogram/ boxplot/ scatter/ density etc)
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Important Packages for Exploratory Analysis (NumPy Arrays, Matplotlib, seaborn, Pandas and SciPy. stats etc)
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Supervised Machine Learning techniques – what is it?
Supervised Machine Learning techniques – what is it?
EDA, Train, Test & Validation splits
EDA, Train, Test & Validation splits