This program teaches the foundational concepts, theory, and techniques you need to know to become an effective data analyst. Participants will analyze various datasets, built a handful of applications, and applied machine learning algorithms in meaningful ways to get real results. Along the way, participants learn the best practices and computational techniques used by professional data scientists.
From there, the data wrangling topics and lab exercises provide an understanding of the processes used along with the knowledge of the most popular tools and techniques in the domain. The Python content here further demonstrates how to use the Python back-end and extract/transform data from an array of sources including the Internet.
This program covers the following key areas and topics:
- Getting started with Python
- Working with the Python Interactive Shell and Writing and Running Simple Scripts
- Data Types
- Control Statements
- Functions
- Lists and Tuples
- Dictionaries and Sets
- Object-Oriented Programming
- Modules, Packages, and File Operations
- Error Handling
- PCAP Exam Objectives
- PCEP Exam Objectives
- Python for Data Wrangling
- Lists, Sets, Strings, Tuples, and Dictionaries
- Advanced Data Structures and File Handling
- Introduction to NumPy, Panndas, and Matplotlib
- A Deep Dive into Data Wrangling with Python
- Getting Comfortable with Different Kinds of Data Sources
- Learning the Hidden Secrets of Data Wrangling
- Advanced Web Scraping and Data Gathering
- RDMBS and SQL
- "Real Life" Data Wrangling Applications
As part of this program, Learners will complete the following hands-on labs and activities:
- Using the print Method
- Displaying a Statement Multiple Times
- Using Variable Assignment, Using Variables and Assigning Statements
- Displaying the Multiplication Table
- Using Arithmetic Operators
- Performing String Slicing Tasks
- Working with Strings and Manipulating Strings Using the strip Method
- Working with Lists
- Using Boolean Operators
- Working with the if Statement and while Statement
- Using the for Loop and the range Function
- Using Nested Loops
- Working with Function Arguments
- Using Lambda Functions
- Using List Methods and Tuple Methods
- Arranging and Presenting Data Using Dictionaries
- Combining Dictionaries
- Creating Intersections of Elements in a Collection
- Defining Methods in a Class
- Creating Class Attributes, Class Methods and Using Information Hiding
- Overriding Methods
- Practicing Multiple Inheritance
- Using Resources in a Module
- Identifying Error Scenarios
- Handling Errors
- Creating the Custom Exception Class
- Sorting and Generating a List
- Deleting a Value, Accessing and Setting Values in/from a Dictionary
- Slicing/Splitting a String
- Implementing a Queue
- Implementing Multi-Element Membership Checking
- Implementing a Stack
- Opening a File and Printing its Content
- Generating Arrays Using arange and linspace
- Multiplying Two Arrays
- Adding Two NumPy Arrays
- Creating a NumPy Array
- Filtering Elements from a Matrix
- Stacking Arrays
- Subsetting a DataFrame
- Grouping a DataFrame
- Dropping the Missing Values
- Replacing Missing Values in a DataFrame
- Joining DataFrames
- Concatenating Data Frames
- Counting Values
- Bypassing the Headers of a CSV File
- Reading Data from a CSV File
- Stacking URLs from a Document Using bs4
- Counting Tags
- Using the zip Function
- Using a One-Liner Generator Expression
- Using a Generator Expression
- Using the format Function
- Using a Box Plot
- Checking the Status of the Web Request
- Extracting Text from a Section
- Traversing an XML Tree
- Checking Whether the Input String Begins with a Specific Word
- Matching Pattern
- Finding the Number of Words in a List That End with ing
- Deleting the Data
- Using Joins
- Using the Foreign Key
- Updating Data
- Using the ORDER BY Clause
- Using the SELECT Statement
- Skipping the First Row of the Data Set
Optional Volunteer Externship Opportunity
Learners who complete this program are eligible to participate in an optional volunteer externship opportunity with a local company/agency/organization whose work aligns with this area of study in order to gain valuable hands-on experience. As learners progress through their eLearning program, an Externship Coordinator will reach out to coordinate placement.
Note: Additional documentation including health records, immunizations, drug-screening, criminal background checks, etc. may be required by the externship facility.