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Python and Pandas

Unlock the power of data with our comprehensive course on Python and Pandas! Designed for beginners and intermediates alike, this course will guide you through the fundamentals of Python programming and its application in data analysis using the Pandas library.

5.0
1,000+ Students
100% Live Lectures
12 months | Installments allowed
Mentor: Dr. Richards M.
Python & Pandas preview
40% OFF Limited time
₦380,000
₦179,999
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PythonPandas
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About this course

You will start by learning Python basics, including data types, control structures, and functions. Then, you will delve into Pandas to perform data manipulation, cleaning, and analysis. With hands-on projects and real-world datasets, you will gain practical experience in handling data, performing exploratory data analysis (EDA), and visualizing results.

By the end of this course, you will be equipped with the skills to analyze complex datasets efficiently and make data-driven decisions across various domains. Join us to elevate your data analysis skills and embark on your journey in the data science field!

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Requirements

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Course curriculum — 7 modules

Module 1
Introduction to Python
  • Introduction to Python: Overview and setup
  • Jupyter Notebooks / Anaconda: Installation, features, and usage
  • Variables in Python: Declaring and using variables
  • Variable Best Practices: Guidelines for naming conventions and usage
  • Camel Case (camelCase), Pascal Case (PascalCase), Snake Case (snake_case)
  • String Concatenation: Combining strings in Python
  • Variables for Arithmetic: Using variables in mathematical operations
  • Multiple Variables Assignment: Assigning values to multiple variables simultaneously
  • Print Statements: Outputting data to the console
  • String Merging with Variables: Embedding variables inside strings
Module 2
Data Types in Python
  • Numeric Data Types: Integers, Floats, Complex numbers
  • Sequence Data Types: Strings, lists, tuples
  • Boolean Data Type: True and False values
  • Set Data Type: Definition and operations
  • Dictionary Data Type: Key-value pairs
  • Best Practices for Data Types: Efficient and appropriate usage
  • List Data Types: Creation, manipulation, and indexing
  • Nested Lists: Working with lists within lists
  • Indexing and Slicing: Accessing elements in sequences
  • Tuples: Immutable sequences
  • Sets: Unordered collections of unique elements
Module 3
Control Flow in Python
  • Comparison Operators: Equality, inequality, greater than, less than
  • Logical Operators: AND, OR, NOT
  • Membership Operators: in, not in
  • Conditional Statements: if, else, elif
  • For Loops: Iterating over sequences
  • While Loops: Repeating actions based on a condition
  • Functions in Python: Defining and using functions
Module 4
Python Projects & Web Scraping
  • Data Type Conversions: Changing between different data types
  • Project 1: Building a BMI Calculator
  • Project 2: Building an Automated File Sorter for File Explorer
  • Project 3: Web Scraping Basics with HTML
  • Introduction to BeautifulSoup + Requests
  • Using find() and find_all() in web scraping
  • Project 4: Scraping Data from a Real Website
Module 5
Pandas for Data Analysis
  • Introduction to Pandas: Setting up and reading data
  • Reading Files: Loading CSV, Excel, and other formats
  • Filtering Columns and Rows: Accessing and manipulating specific data
  • Indexes in Pandas: Setting and using indexes
  • Group By and Aggregate Functions: Summarizing data
  • Merging DataFrames: Combining data from multiple sources
Module 6
Data Analysis Projects with Pandas
  • Project 5: Creating Visualizations using Pandas
  • Project 6: Data Cleaning and Preparation in Pandas
  • Project 7: Exploratory Data Analysis (EDA)
  • Project 8: Amazon Web Scraping using Python
  • Project 9: Automating Cryptocurrency Website API Pull using Python
Module 7
Portfolio Project
  • Final Portfolio Project: Build a comprehensive project showcasing all learned skills, with a focus on real-world applications (e.g., data analysis, web scraping, automation)
Dr. Richards M.
Data Engineer · University of Derby, UK
5.0  ·  1,000+ Students

Dr. Richards M. is a skilled Data Analytics professional with a Master's in Big Data Analytics from the University of Derby, UK. He has expertise across various Engineering Tech Stacks, contributing to process optimization and market enhancement for organizations, with a strategic approach focused on business growth and efficiency.

Student reviews

Adenike Idowu
4.9
Empowering and Educative!

Dr. Richards M. is a skilled Data Analytics professional with a Master's in Big Data Analytics from the University of Derby, UK. He has expertise across various Engineering Tech Stacks, contributing to process optimization and market enhancement for organizations, with a strategic approach focused on business growth and efficiency.

Wivina Omolemen
4.9
Life-Changing Educational Journey!

As a recent graduate, Vephla University played an instrumental role in my academic success. The interactive learning modules made difficult concepts easier to grasp, and I loved how I could learn at my own pace.

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