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Week 2

Initial Post

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.

Why are statistical programming languages important to data scientists? What are some advantages and disadvantages the R programming language has over the other main statistical programming languages (i.e. Python, SAS, SQL)?

Reply Post

When replying to a classmate, offer your opinion on what they posted comparing the R programming language to the other statistical programming languages. Using at least 3 – 5 sentences, explain why you agreed or disagreed with their evaluation of the different statistical programming languages.

Discussion 2 (Chapter 2): Discuss the process that generates the power of AI and discuss the differences between machine learning and deep learning. Note: The first post should be made by Wednesday 11:59 p.m.,

Chapter 2 – Discussion question #1 &

Discuss the difficulties in measuring the intelligence of


                    Exercise question #4 &4. In 2017, McKinsey & Company created a five-part video

titled “Ask the AI Experts: What Advice Would You Give

to Executives About AI?” View the video and summarize

the advice given to the major issues discussed. (Note:

This is a class project.)

                    Exercise question #5 &5. Watch the McKinsey & Company video (3:06

min.) on today’s drivers of AI at youtube.com/

watch?v=yv0IG1D-OdU and identify the major AI

drivers. Write a report.

                    Exercise question 15 (limit to one page of analysis for question 15)15. Explore the AI-related products and services of Nuance

Inc. (nuance.com). Explore the Dragon voice recogni

tion product.