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Course Duration:2 Weeks

Course Details

10 Days of Data Crunching Awesomeness ● Python For Data Science Crash course ● Numpy Matplotlib Pandas ● Data Analysis - Exploration and Wrangling ● Data Visualization ● Data Mining ● Machine Learning 
Day One - Python Crash Course ● Dictionaries ● Sets ● Tuples ● Lists ● List Comprehensions ● Iterators ● Generators ● Lambda Functions 
Day Two - Crash Course contd. ● Functions as variables and parameters ● Embedding and Returning functions ● Maps and Filters ● Zip and izip ● Array processing ● Column Preprocessing ● List Sorting ● Itertools
Day Three - Using Numpy and Matplotlib ● Introduction to NumPy ● Numpy Arrays ● Numpy Array Indexing ● Numpy Operations and Exercises ● Introduction to Matplotlib ● Matplotlib Overview ● Matplotlib Exercises 
Day Four - Pandas ● Introduction to Pandas ● Series and Data Frames ● Missing Data ● Groupby ● Merging Joining Concatenating ● Pandas operations ● Data Input and Output ● Exercises 
Day Five - Data Analysis Exploration ● Analyzing Univariate Data Graphically ● Grouping data and using plots ● Using scatter plots ● Using heatmaps ● Summary statistics ● Summary plots ● Box and Whisker plot 
Day Six - Data Exploration and Wrangling ● Impute the Data ● Scaling Data ● Standardizing Data ● Language Processing ● Tokenization ● Stopping and stemming words ● Word clouds 
Day Seven - Data Mining ● Distance Measures ● Kernel Methods ● Clustering Data using k-means ● Learning vector quantization ● Finding outliers 
Day Eight - Machine Learning ● Introduction ● Data preparation ● Finding nearest neighbours ● Document classification ● Naive Bayes ● Decision Trees
Day Nine - Machine Learning ● Introduction ● Prediction using Regression ● Regression with L2 shrinkage ● Regression with L1 shrinkage ● LASSO ● Cross Validation 
Day Ten ● Review ● Mini project ● Discussion of further learning.

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