Python Data Analysis Training

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Python Data Analysis Training

D ata analysis course teaches some of the most important techniques and tools necessary to manipulate and analyze large datasets and summarize conclusions. This includes:

  • exploratory and predictive statistics
  • more advanced computer program design
  • an introduction to algorithms
  • python for statistical analysis
  • data visualization best practices
Python Data Analysis Training
Course Content

  • Understanding Data Analysis
  • How python is used for Data Analysis
IPython Basics

  • IPython Basics
  • IPython HTML Notebook
  • Advanced IPython Features
NumPy Basics

  • The NumPy ndarray
  • Data types for ndarrays
  • Arrays and Scalars
  • Indexing and Slicing
  • Fast element wise array functions
  • Data Processing
  • Linear Algebra
  • Random number generation
Working with pandas

  • Pandas data structures
  • Series
  • DataFrame and Index Objects
  • Reindexing
  • Sorting and Ranking
  • Handling missing data
  • Hierarchical Indexing
Data Loading, Storage, File Formats

  • Reading and Writing data in text format
  • Binary Data Format
  • Interacting with the databases
Data Wrangling

  • Combining and merging data sets.
  • Pivoting
  • Transforming the data
  • String manipulation
Plotting and Visualization

  • matplotlib
  • Plotting functions in pandas
  • Plotting maps
Data Aggregation and Group Operations

  • GroupBy
  • Data Aggregation
  • Group wise operations
  • Pivot Tables
Time Series

  • Date and Time types
  • Time basics
  • Date basics
  • Period Arithmetic
  • Time Series Plotting
Financial and Economic Data Applications

  • Data Munging
  • Group Transforms and Analysis
  • Rolling Correlation and Linear Regression
NumPy Advanced

  • Advanced Array Manipulation
  • Broadcasting
  • Structured and Record Arrays
  • NumPy matrix class
  • Sorting
  • This course is intended for people with little to no background in data analysis and computer programming.
  • An introductory statistics class and an introductory programming class will both come in handy, but are not necessary.
  • A basic familiarity with calculus and general computer competency is assumed.
  • To develop relevant programming abilities.
  • To demonstrate proficiency with statistical analysis of data.
  • To develop the ability to build and assess data-based models.
  • To execute statistical analyses with professional statistical software.
  • To demonstrate skill in data management.
Know More about Course Duration, Sessions and latest offers
  • Cyber Metric Services
  •   8/1, 5th Main Rd, Ganganagar,
         R.T.Nagar, Bangalore-560032,
         Karnataka, India
  •   30/1, 4th Stage, Industrial Town,
         Basaveshwara Nagar, W C R,
         Rajajinagar, Bangalore – 560010,
         Karnataka, India

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