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Python for Data Science: Panda, NumPy and Matplotlib


This a two-day course that provides an overview of how Python can be used in Data Science to manipulate, process, clean, and crunch data.

It is an introduction to scientific computing in Python focusing data-intensive applications. This course will review the essential Python libraries:

  • NumPy
  • Pandas
  • Matplotlib
  • IPython
  • SciPy

Students wanting use Python in data analytics applications.


It is recommended that students that are interested in this course have:  

  • Introductory Python course/s
  • Six months of Python programming experience.


Module 1: Building Blocks

  • Working with Python
  • Numpy Ndarrays
  • Slicing and indexing
  • Scalar Operations
  • Shape Shifting
  • Descriptive Statistics
  • Array Operations
  • Multiple Dimensions
  • Array Creation Options
  • Data Types
  • Getting Numpy-Specific Help
  • Overview of Data Visualization/Presentation tools

Module 2: Overview of Pandas

  • Working with Pandas in an IDE
  • Enhancements from Ndarray Objects
  • Series Objects
  • Pandas in 2-D
  • Pandas in 3-D

Module 3: Data Acquisition N

  • Dealing with missing Data and Outliers
  • Slicing, Dicing, and Re-Indexing
  • Data description/Analysis Tools

Module 4: Data Visualization

Module 5: DataTime-Like Objects

  • Basic time series Operations
  • Introspecting Time Series
  • Tools for Holidays, Business Day, Etc. .
  • Comparing and combining Data from different Series
  • Time shifting and time “Window” Operations

Module 6: Pandas Database OPS

  • Comparison of SQL Operations and Pandas Methods
  • Creating Pivot Tables and Cross-Tabulations
  • Aggregating data across different tables
  • Creating complex queries with intermediate Data frame Objects

Module 7: Pandas + Machine Learning tools

  • What is LDA?
  • Getting to know the data
  • Exploring data integrity
  • Applying the LDA Model
  • Do you want a doggie bag?
  • Quick recap of the analysis

Review A: Text-only debugging

  • The PDB debug library
  • Other text-based tools
  • Integrating logging with debugging

Review B:  Introduction to Bayesian Analysis

  • A simple real-life example
  • The Bayesian approach
  • Reality checking

What's included?

  • Authorized Courseware
  • Intensive Hands on Skills Development with an Experienced Subject Matter Expert
  • Hands on practice on real Servers and extended lab support 1.800.482.3172
  • Examination Vouchers  & Onsite Certification Testing- (excluding 1-day Adobe, 1-day MS Office and PMP Boot Camps) 
  • Academy Code of Honor: Test Pass Guarantee
  • Optional: Package for Hotel Accommodations, Lunch and Transportation

Training Formats

With several convenient training delivery methods offered, The Academy makes getting the training you need easy. Whether you prefer to learn in a classroom or an online live learning virtual environment, training videos hosted online, and private group classes hosted at your site. We offer expert instruction to individuals, government agencies, non-profits, and corporations. Our live classes, on-sites, and online training videos all feature certified instructors who teach a detailed curriculum and share their expertise and insights with trainees. No matter how you prefer to receive the training, you can count on The Academy for an engaging and effective learning experience.


Instructor Led (the best training format we offer)
Live Online Classroom – Online Instructor Led
Self-Paced Video

Speak to an Admissions Representative for complete details

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