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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.
The trainer was very knowledgeable and gave all the necessary tips to attend for the test. However, the training material would've been good if some more examples we're given... Otherwise all good.Attended workshop in January 2018
The training was very engaging and informative. The scrum framework in general and the Product Owner role in detail were explained by actually applying the framework to the training. Though the attendees were from many different professional backgrounds and had different knowledge levels about Scrum, the trainer was able to touch upon each and every question that was asked. I would definitely recommend taking the training with Knowledgehut.Attended workshop in July 2018
The best professional training I have ever attended! A lot of positive energy and concepts from the trainer "Stuart Mitchell". Also, the facilities and arrangements were excellent.Attended workshop in July 2018
This training, that I attended was with around 70-80 people. the trainer Madhur, ho man he is so awesome, he helped us correct our thought on Scrum, he never made us feel that we were in a training it was more of a session where we were changing out thought and hence learning with ease. It was a really well-organized session, and at a nice hotel. it was a 100% result. now I am a CSM. Thank you.Attended workshop in July 2018
To attend this course, candidates must have
Data mining and analytics comes with great potential to help companies, as they can extract hidden predictive data from large databases and use it to predict future trends and behaviors. Data mining tools are able to find answers to questions that were earlier considered too time consuming to resolve. This allows businesses to make proactive, data-driven decisions and enhance viable business opportunities.
Our expert facilitators will help you understand how to collect and refine massive amounts of information, and discover hidden value in your warehouse of data. You will increase your employment opportunities, as you can put yourself on the radar of corporate businesses looking for data experts.
On successful completion of the course, you will receive a Course Completion Certificate from KnowledgeHut with Credits (1 credit per hour of training).
Any registration cancelled within 48 hours of the initial registration will be refunded in FULL (please note that all cancellations will incur a 5% deduction in the refunded amount due to transactional costs applicable while refunding). Refunds will be processed within 30 days of receipt of written request for refund. Kindly go through our Refund Policy for more details: http://www.knowledgehut.com/refund
Please send in an email to email@example.com, and we will answer any queries you may have!
To attend this course, candidates must have prior programming knowledge and knowledge of RDMS. This course is suggested for