Details
The need for data harvesting and mining is growing in a broad range of areas, ranging from banking to insurance, retail, telecom, medicine, research, and government. This course provides aspiring data engineers and data scientists with the knowledge and tools they need to do proper data ingestion and analytics using R. R is a free software environment for statistical computing and graphics that is growing in popularity, as it gives quick results and is well supported by a worldwide community of users and developers.
By scouring databases for hidden patterns, data mining experts can find predictive information that helps to make informed business decisions and enhance profitability. You will understand practical and efficient methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Participants will be introduced to data scraping, APIs, and parsing along with various topics in data analytics such as statistical analysis, plotting, linear regression/ANOVA, PCA (Principal Component Analysis), Clustering, Factor Analysis, and time series/ARIMA. An overview of data scraping and parsing in Python using BeautifulSoup is also covered.
On successful completion of the course, you will receive a Course Completion Certificate from KnowledgeHut.
What you will learn:- Use of rvest and BeautifulSoup for data scraping
- Connecting to APIs and feeds
- ETL, Data preparation, cleansing, and structuring in R
- EDA (Exploratory Data Analysis) in R
- Graphing in R
- Linear regression/ANOVA
- Time Series/ARIMA
- Comprehensive, downloadable courseware
- In-depth case studies for better retention
- Course completion certificate
- 1 credit per hour of learning
- 5 days of quality interactive learning
- Course completion certificate
- Get deep insights into best practices in Data harvesting and analytics using R
- Covers practical and efficient methods for applying R to extract data
- Downloadable comprehensive courseware
- Hands-on exercises to cement your learning
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