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. Program Objectives Skills-Based Labs and Activities 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 Job and Externship Placement Services Regardless if you elect to pursue national certification or not, if you enroll and successfully complete this program, assuming you pass a background check and drug screen, you will have guaranteed access to our Ready to Work (RTW) Job and Externship Placement services. All students who successfully complete this program (and pass a background check and drug screen) will have access to the RTW Externship or Job placement services at no additional cost.
