Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn.

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* Actual course outline may vary depending on offering center. Contact your sales representative for more information.

Learning Objectives

Working in a hands-on learning environment, guided by our expert team, attendees will learn to:
Understand how data analysts and scientists gather and analyze data
Perform data analysis and data wrangling using Python
Combine, group, and aggregate data from multiple sources
Create data visualizations with pandas, matplotlib, and seaborn
Apply machine learning (ML) algorithms to identify patterns and make predictions
Use Python data science libraries to analyze real-world datasets
Use pandas to solve common data representation and analysis problems
Build Python scripts, modules, and packages for reusable analysis code
Perform efficient data analysis and manipulation tasks using pandas
Apply pandas to different real-world domains with the help of step-by-step demonstrations
Get accustomed to using pandas as an effective data exploration tool.

1
  • INTRODUCTION TO DATA ANALYSIS

  • Fundamentals of data analysis

    Statistical foundations

    Setting up a virtual environment


2
  • WORKING WITH PANDAS DATAFRAMES

  • Pandas data structures

    Bringing data into a pandas DataFrame

    Inspecting a DataFrame object

    Grabbing subsets of the data

    Adding and removing data


3
  • DATA WRANGLING WITH PANDAS

  • What is data wrangling?

    Collecting temperature data

    Cleaning up the data

    Restructuring the data

    Handling duplicate, missing, or invalid data


4
  • AGGREGATING PANDAS DATAFRAMES

  • Database-style operations on DataFrames

    DataFrame operations

    Aggregations with pandas and numpy

    Time series


5
  • VISUALIZING DATA WITH PANDAS AND MATPLOTLIB

  • An introduction to matplotlib

    Plotting with pandas

    The pandas.plotting subpackage


6
  • PLOTTING WITH SEABORN AND CUSTOMIZATION TECHNIQUES

  • Utilizing seaborn for advanced plotting

    Formatting

    Customizing visualizations


7
  • FINANCIAL ANALYSIS - BITCOIN AND THE STOCK MARKET

  • Building a Python package

    Data extraction with pandas

    Exploratory data analysis

    Technical analysis of financial instruments

    Modeling performance


8
  • RULE-BASED ANOMALY DETECTION

  • Simulating login attempts

    Exploratory data analysis

    Rule-based anomaly detection


9
  • GETTING STARTED WITH MACHINE LEARNING IN PYTHON

  • Learning the lingo

    Exploratory data analysis

    Preprocessing data

    Clustering

    Regression

    Classification


10
  • MAKING BETTER PREDICTIONS - OPTIMIZING MODELS

  • Hyperparameter tuning with grid search

    Feature engineering

    Ensemble methods

    Inspecting classification prediction confidence

    Addressing class imbalance

    Regularization


11
  • MACHINE LEARNING ANOMALY DETECTION

  • Exploring the data

    Unsupervised methods

    Supervised methods

    Online learning


12
  • THE ROAD AHEAD

  • Data resources

    Practicing working with data

    Python practice


Audience

This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets.

Language

English

Prerequisites

Students should have skills at least equivalent to the following course(s) or should have attended as a pre-requisite: TTDS6600 Understanding Data Science | A Technical Overview – 1 day (helpful but not required) TTPS4800 Introduction to Python Programming (3 days)

$2,195

Length: 3.0 days (24 hours)

Level:

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06
Dec
Wednesday
10:00 AM ET -
6:00 PM ET
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