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    Python & Data Science with R | Python & R Programming

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    Programming Languages · Online Course

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    This comprehensive dual-language course, designed by Oak Academy, serves as an exceptional bridge for aspiring data professionals looking to master both Python and R programming. In the modern data landscape, proficiency in both environments is a massive competitive advantage. Students begin their journey with a robust environment setup, installing Anaconda across Windows, macOS, or Linux, before diving deep into the fundamentals of Python syntax. The curriculum meticulously breaks down complex coding concepts, from basic data structures, PEP 8 styling guidelines, and variable assignment to sophisticated string operations, indexing, and advanced formatting methods like f-strings. Learners will master control flow structures - including nested conditional statements and versatile loops - and then transition into writing efficient, reusable code with functions, lambda expressions, and Object-Oriented Programming (OOP) principles. By combining these core Python competencies with targeted R programming foundations, the course equips learners with the versatile tools required for end-to-end data analytics and predictive modeling. Whether you are transitioning into tech or seeking to expand your existing analytical toolkit, this course offers the practical, project-based guidance necessary to build a portfolio of actionable data skills.

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    Oak Academy

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    Oak Academy is an elite group of tech professionals, software engineers, and digital designers dedicated to bridging the gap between theoretical knowledge and real-world execution. With a wide-ranging curriculum that spans from Generative AI engineering and data science to full-stack web development and UI/UX design, the academy provides modern learners with the in-demand technical skills required in today's rapid job market. Their teaching methodology focuses on active learning, where abstract coding principles, AI configurations, and design systems are broken down into digestible, step-by-step modules. Students don't just watch videos; they build responsive websites, engineer prompts for advanced AI pipelines, design…Show more

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    Program Overview

    Online Course

    Learning format

    Programming Languages

    Subcategory

    $49.99

    Price

    Price may change · updated within 1–2 weeks

    English

    Course language

    What You'll Learn

    • Installing Anaconda Distribution for Windows
    • Installing Anaconda Distribution for MacOs
    • Installing Anaconda Distribution for Linux
    • Reviewing The Jupyter Notebook
    • Reviewing The Jupyter Lab
    • Python Introduction
    • First Step to Coding
    • Using Quotation Marks in Python Coding
    • How Should the Coding Form and Style Be (Pep8)
    • Introduction to Basic Data Structures in Python
    • Performing Assignment to Variables
    • Performing Complex Assignment to Variables
    • Type Conversion
    • Arithmetic Operations in Python
    • Examining the Print Function in Depth
    • Escape Sequence Operations
    • Boolean Logic Expressions
    • Order Of Operations In Boolean Operators
    • Practice with Python
    • Examining Strings Specifically
    • Accessing Length Information (Len Method)
    • Search Method In Strings Startswith(), Endswith()
    • Character Change Method In Strings Replace()
    • Spelling Substitution Methods in String
    • Character Clipping Methods in String
    • Indexing and Slicing Character String
    • Complex Indexing and Slicing Operations
    • String Formatting with Arithmetic Operations
    • String Formatting With % Operator
    • String Formatting With String Format Method
    • String Formatting With f-string
    • Method Creation of List
    • Reaching List Elements – Indexing and Slicing
    • Adding & Modifying & Deleting Elements of List
    • Adding and Deleting by Methods
    • Adding and Deleting by Index
    • Other List Methods
    • Creation of Tuple
    • Reaching Tuple Elements Indexing And Slicing
    • Creation of Dictionary
    • Reaching Dictionary Elements
    • Adding & Changing & Deleting Elements in Dictionary
    • Dictionary Methods
    • Creation of Set
    • Adding & Removing Elements Methods in Sets
    • Difference Operation Methods In Sets
    • Intersection & Union Methods In Sets
    • Asking Questions to Sets with Methods
    • Comparison Operators
    • Structure of “if” Statements
    • Structure of “if-else” Statements
    • Structure of “if-elif-else” Statements
    • Structure of Nested “if-elif-else” Statements
    • Coordinated Programming with “IF” and “INPUT”
    • Ternary Condition
    • For Loop in Python
    • For Loop in Python(Reinforcing the Topic)
    • Using Conditional Expressions and For Loop Together
    • Continue Command
    • Break Command
    • List Comprehension
    • While Loop in Python
    • While Loops in Python Reinforcing the Topic
    • Getting know to the Functions
    • How to Write Function
    • Return Expression in Functions
    • Writing Functions with Multiple Argument
    • Writing Docstring in Functions
    • Using Functions and Conditional Expressions Together
    • Arguments and Parameters
    • High Level Operations with Arguments
    • all(), any() Functions
    • map() Function
    • filter() Function
    • zip() Function
    • enumerate() Function
    • max(), min() Functions
    • sum() Function
    • round() Function
    • Lambda Function
    • Local and Global Variables
    • Features of Class
    • Instantiation of Class
    • Attribute of Instantiation
    • Write Function in the Class
    • Inheritance Structure

    Best For

    • Aspiring data scientists who want to master both Python and R simultaneously.
    • Beginners looking to build a strong foundation in programming syntax and logic.
    • Data analysts who need to manage data environments using Anaconda and Jupyter.
    • Professionals transitioning into technical roles requiring versatile data manipulation tools.

    Not For

    • Advanced developers already proficient in both Python and R seeking high-level machine learning algorithms.
    • Learners who prefer a course focused exclusively on one language rather than a dual-language approach.
    • Individuals searching for specialized instruction in big data frameworks like Spark or Hadoop.
    • Software engineers looking for advanced system-level backend development training.

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