Using Python to Control and Document Your Data Science Processes

Data Science with Python Training: Data types and objects

Loading packages, namespaces

Reading and writing data

Simple plotting

Control flow

Debugging

Code profiling

Accessing and Preparing Data

Acquiring Data with Python

• Loading from CSV files
• Accessing SQL databases

Cleansing Data with Python

• Stripping out extraneous information
• Normalizing data
• Formatting data

Numerical Analysis, Data Exploration, and Data Visualization with NumPy Arrays & Matplotlib

The NumPy array

2D plotting with Matplotlib

N-dimensional array operations and manipulations

Memory mapped files

Exploring Data with Pandas and scipy.stats

Data manipulation with Pandas

Statistical analysis with Pandas

Time series analysis with Pandas

Overview of statistical tools in scipy.stats

Machine Learning with scikit-learn

Input: 2D, samples, and features

Pre-processing data

Regression

Classification

Model selection

Duration & Timings :

Duration – 30 Hours.

Training Type: Online Live Interactive Session.

Faculty: Experienced.

Access to Class Recordings.

Weekday  Session –  Mon – Thu 8:30 PM – 10:30 PM EST– 4 Weeks. April 1, 2019.

Weekend Session – Sat & Sun 9:30 AM to 12:30 PM (EST) – 5 Weeks. May 11, 2019.

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