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    Data Science with R and Python | R Programming

    BY
    Udemy

    Using R programming and Python, obtain a hands-on understanding of the core principles and methods involved in data science operations.

    Brochure Enquire
    Mode

    Online

    Fees

    ₹ 2999

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based

    Course overview

    Python offers a more open-ended approach to data science, whereas R programming is mostly utilized for statistical research. Data analysis and statistics are the main goals of R programming, whereas production and deployment are the main goals of Python. Data Science with R and Python | R Programming certification course is developed by Oak Academy, a learning management system that also offers courses in IOS, Android, Ethical Hacking, IT, Web & Mobile Development, and is made available by Udemy.

    Data Science with R and Python | R Programming online course involves 13 hours of prerecorded lectures accompanied by 4 articles and 9 downloadable resources, which is designed for the participants who wish to become certified data scientists by learning the features of Python and R programming. Data Science with R and Python | R Programming online training explains the topics like data visualization, data munging, data analysis, data manipulation, business analytics, data transformation, data frames, Pandas, Numpy, Matplotlib, and more.

    The highlights

    • Certificate of completion
    • Self-paced course
    • 23.5 hours of pre-recorded video content
    • 4 articles
    • 9 downloadable resources

    Program offerings

    • Online course
    • Learning resources
    • 30-day money-back guarantee
    • Unlimited access
    • Accessible on mobile devices and tv

    Course and certificate fees

    Fees information
    ₹ 2,999
    certificate availability

    Yes

    certificate providing authority

    Udemy

    What you will learn

    Data science knowledge Knowledge of python Business analytics knowledge Programming skills R programming Knowledge of data visualization Knowledge of numpy Knowledge of big data Machine learning Financial knowledge

    After completing the Data Science with R and Python | R Programming online certification, participants will acquire a deeper understanding of the core concepts involved with data science using R programming and python. Participants will explore the functionalities of data frames, data structure, arrays, and matrices for data science operations. Participants will gain knowledge of the techniques and procedures used in data transformation, data analysis, data munging, data visualization, and data manipulation, as well as the functionalities of the libraries like pandas, NumPy, and Matplotlib. Participants will also gain a fundamental understanding of the significance of data science in business intelligence, financial analysis, machine learning, and big data.

    The syllabus

    Data Science: Python is Easy To Learn

    • Be Smart and Use Data But How: Answer is Data Science with Python
    • FAQ regarding Data Science
    • FAQ regarding Python and R programming
    • Project Files and Course Documents for Data Science with Python and R

    Setting Up Python for Mac and Windows : Python, Data science, R programming

    • Installing Anaconda for Windows - Python with R Programming, Python
    • Installing Anaconda for Mac - Python R Programming
    • Let's Meet Jupyter Notebook for Windows - Python data science
    • Basics of Jupyter Notebook for Mac - python data science, r programming

    Fundamentals of Python

    • Data Types in Python
    • Operators in Python
    • Conditionals in Python
    • Loops in Python
    • Lists, Tuples, Dictionaries and Sets in Python
    • Data Type Operators and Methods in Python
    • Modules in Python
    • Functions in Python
    • Exercise Analyse in Python Programming
    • Exercise Solution in Python Programming

    Python For Data Science: Data Science

    • What Is Data Science?
    • Data Literacy in Python
    • Python Data Science Quiz

    Using Numpy for Data Manipulation

    • What is Numpy?
    • Array and Features in Python Numpy
    • Array Operators in Python Numpy
    • Indexing and Slicing in Python Numpy
    • Numpy Exercises in Python Numpy

    Pandas: Using Pandas for Data Manipulation

    • What is Pandas?
    • Series and Features in Pandas

    Data Frame with Pandas

    • Data Frame Attributes and Methods in Pandas Python
    • Data Frame Attributes and Methods Part – II in Pandas Python
    • Data Frame Attributes and Methods Part – III in Pandas Python
    • Multi Index in Pandas Python
    • Groupby Operations in Pandas Python
    • Missing Data and Data Munging in Pandas Python
    • Missing Data and Data Munging Part II in Pandas Python
    • How We Deal with Missing Data in Pandas Python?
    • Combining Data Frames in Pandas Python
    • Combining Data Frames Part – II in Pandas Python
    • Work with Dataset Files in Pandas Python
    • Data Science ( Python and R ) Quiz
    • Data Science ( Python and R ) Quiz

    Python For Data Science: Data Visualization

    • What is Matplotlib?
    • Using Matplotlib
    • Pyplot – Pylab - Matplotlib
    • Figure, Subplot and Axes in Python Matplotlib
    • Figure Customization in Python Matplotlib
    • Plot Customization in Python Matplotlib

    Data Science: Hands-On Projects

    • Analyse Data With Different Data Sets: Titanic Project
    • Titanic Project Answers in Data Analysis
    • Project II: Bike Sharing in Data Analysis
    • Bike Sharing Project Answers in Data Analysis
    • Project III: Housing and Property Sales in Data Analysis
    • Answer for Housing and Property Sales Project in Data Analysis
    • Project IV: English Premier League in Data Analysis
    • Answers for English Premier League Project in Data Analysis

    Environment Installation for R

    • Downloading and Installing R & R Studio
    • R Console Versus R Studio

    Data Management in R

    • Getting Data into R
    • Data Manipulation in R programming
    • Graphs and Charts in R programming

    Examining and Managing Data Structures in R

    • Vector Basics in R Programming
    • Atomic Vector Types in R Programming
    • Converting Data Types of Atomic Vectors in R Programming
    • Test Functions in R Programming
    • Vector Recycling and Iterations in R Programming
    • Naming Vectors in R Programming
    • Subsetting Vectors in R Programming

    Lists in R Programming

    • Lists in R Programming

    Arrays in Python R Programming

    • Arrays in Python R Programming
    • Subsections of an Array in Python R Programming

    Matrices in Python R Programming

    • Matrices in Python R Programming
    • Naming Matrix Row and Columns in Python R Programming
    • Calculating With Matrices in Python R Programming

    Data Frames in Python R Programming

    • Introduction to Data Frames in Python R Programming
    • Naming Variables and Observations in DF in Python R Programming
    • Manipulating Values in DF
    • Adding and Removing Variables in Python R Programming
    • Tibbles in R

    Factors in Python R Programming

    • Introduction to Factors
    • Manipulating Categorical Data with Forcats

    Data Transformation in R

    • Introduction to Data Transformation in R
    • Select Columns with Select Function in R
    • Filtering Rows with Filter Function in R
    • Arranging Rows with Arrange Function in R
    • Adding New Variables with Mutate Function in R
    • Grouped Summaries with Summarize Function in R

    Bonus - Data science, R programming, Python and R

    • Bonus - Python data science, python and r, R programming

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