Brochure
Enquire- Introduction to Python and R
- Course Outline
Data Analysis using Python and R for Absolute Beginner.
BY
Udemy
Develop a thorough understanding of the principles and procedures associated with data analysis through the use of r ...Read more
Beginner
Online
₹ 3499
Quick Facts
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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Course overview
Both Python and R are fantastic languages for performing data analysis. Additionally, they are both excellent for those who have never programmed before. Fortunately, there are a variety of resources and materials available to assist people along the path, regardless of whatever language they decide to learn originally. Piyush S, a data scientist, engineer, and project manager, designed the Data Analysis using Python and R for Absolute Beginner[2022] online certification, which is provided by Udemy.
Data Analysis using Python and R for Absolute Beginner[2022] online classes incorporates more than 12.5 hours of detailed lectures supported by articles, 36 downloadable resources, assignments, and case studies on bank marketing, uber supply demand, car datasets, and more. Data Analysis using Python and R for Absolute Beginner[2022] online training provides a deeper comprehension of the fundamentals of Python and R programming for data analysis operations, which also covers topics like data visualization, exploratory data analysis, website scraping, data extraction, and data cleaning.
The highlights
- Certificate of completion
- Self-paced course
- 12.5 hours of pre-recorded video content
- 1 article
- 37 downloadable resources
- Assignments
- Case studies
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
₹ 3,499
certificate availability
Yes
certificate providing authority
Udemy
Who it is for
What you will learn
Data science knowledge
Knowledge of python
R programming
Knowledge of numpy
Knowledge of data visualization
After completing the Data Analysis using Python and R for Absolute Beginner[2022] certification course, students will master the principles of data analysis using python and R programming or data science operations. Students will explore extrapolatory data analysis, data visualization, data cleaning, data extraction, and RDBMS methods. Students will learn about the capabilities of libraries such as Pandas and NumPy, as well as the capabilities of visualization charts, box plots, bar charts, and data frames in data analysis for making business decisions.
The syllabus
Introduction
Introduction-Python
- Installation of Developer Environment -Anaconda & Jupyter
- Crash Course -1 : Python Basic Program
- Crash Course -2 : Python Basic Program
- Python Basics
Python Data Types
- Introduction to Python List
- Understanding Python List
- Introduction to Tuples
- Understanding Tuples
- Python List and Tuples
- Introduction to Dictionary
- Understanding Dictionary
- Dictionary
- Python Sets
Control Structure in Python
- If else Conditions - Decisions Making
- Testing you Decision Making Skills (If elif If )
- Python Loops- Intro
- Understanding For and While Loop
- Python Comprehensions-Intro
- Comprehension ; Loops in List,Dictionary
- Python Function-Intro
- Understanding Python Function
- Map,Reduce,Filter -Introduction
- Map,Reduce ,Filter -Using Lambda Functions
- Assignment-Map Reduce Filter
Python NumPy
- Introduction to NumPy
- Basics of NumPy
- Structures and Contents of Arrays
- Slice and Dice
- NumPy Arrays-Operations
Python PANDAS
- Introduction to the World of Pandas
- Pandas- Series and Dataframes
- Pandas- File upload and DATA Analysis
- Indexing Dataframe
- Merging Dataframes and Arithmetics
- Summarizing , Group by ,Pivoting
Data Extractions and Website Scrapping
- Intro to Data Extraction
- Reading Delimited files and RDBMS data
- Scrapping Websites
Data Cleaning for Data Analysis / Business Insights
- Data Cleaning -Introduction
- Imputing Missing Values Techniques - Melbourne Real Estate Data-1
- Imputing Missing Value - Melbourne Real Estate Data-2
Data Visualizations
- Introduction to the world of Visualization
- Types of Plots
- Matplotlib Basics
- Matplotlib-Marketing Data Plots ( Boxplots, Histograms, Scatter)
- Searborn-Basics - Beautify the plots ( Boxplots, histograms, scatter )
- Seaborn-Correlation Matrix
- Aggregators Plots ( Bi-variate Analysis ) - Bar Charts , Boxplots , Histograms
- Timeseries Plots - Heatmap Plots
Extrapolatory Data Analysis - Case Study (Car Price Data Sets )
- Understanding Data and uploading
- Data Manipulation and Analysis-1
- Data Manipulation and Analysis-2
- Data Cleaning
- PPT Presentation to Business Users for Data Insights
Extrapolatory Data Analysis for Covid 19 ( Case Study )
- Introduction to Case Study for Covid 19
- Analysis and Visualizations for Covid19 Datasets
R - Introduction
- Introduction to the Course - R
- Installation of R and R Studio
- Understanding R Studio
- Understanding Datatypes in R
- Crash Course in R - 1
- Basics of R - 1
- Crash Course in R - 2
- Crash Course in R - 3
- Introduction to Vectors
- Vectors in R - 1
- Vectors in R - 2
- Vectors
- Factors in R -1
- Factors in R -2
- Factors
- Introduction to Matrices
- Matrices
Dataframes in R
- Introduction to Dataframes
- Creating Dataframes
- Accessing Dataframes
- Operations in Dataframes
- Dataframes
- File Upload into Dataframe
- Introduction to List
- List
Constructs in R programming
- Introduction to Constructs in R
- Relational and Logical Operators
- Logical operators
- Conditional Statements - 1
- Conditional Statements
- Understanding Bank File for Credit Card
- Writing Conditions for Credit Card Issuance
- Loops
- Loops-2
- Introduction to Functions
- Functions - Built-in
- Create Your own Functions
- Sapply Functions
Visualizations in R
- Introduction to the world of Visualization - R
- R base Plots-1
- R base Plots-2
- Introduction to ggplot
- Getting Started with ggplots
- Scatter Plots Using ggplot
- Plotting values on ggplot in Scatter plots
- ggplot on Large Datasets
- ggplot as Object
- Plotting Bar Charts using ggplot
- Jitters in ggplot
- Dodge Plots
- Histograms using ggplot
- Timeseries Plots
R - Case Study- Uber Demand Supply Gap
- Understanding Business Problem
- Uber Datasets
- Data Analysis - 1
- Data Visualisations -1
- Data Visualisations - 2
SQL in Python and Data Visualizations
- Introduction to SQL with Python and R
- SQL Python-Upload Market Data
- Write SQL in Python
- Visualizations in Python- Seaborn and Pandas
- MySQL Database Connection with Python
SQL in R and Data Visualizations
- Upload CSV files in R and SQL Queries
- Data Visualizations in R using ggplot
- Connecting MySQL with R and DML operations
- Connecting MySQL with R and DDL operations
Investment Case Study using Excel
- Introduction to Investment Case Studies
- Understanding Case Studies and Downloads
- Data Preparation-1
- Data Preparation - 2
- Data Preparation - 3
- Data Preparation - 4
- Data Preparation - 5
- Country Wise Analysis
- Investment Type Analysis
- Company Category Type Analysis
- PPT Presentation to Business Users for Data Insights
Build your 1st Machine Learning Model - Bonus Lecture
- Understanding Machine Learning
- Introduction to Linear Regression
- CSV file Upload and Data Analysis
- Data Visualisations
- Model Building
- Assumptions of Linear Regression
- Model Fitness and Validation - 1
- Model Fitness and Validation - 2
Instructors
Articles
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