CIS 528 Introduction to Big Data Computing and Analysis (Syllabus) Jongwook Woo, PhD jwoo5@calstatela.edu California State University, LA Computer and Information System Department ‹#› 1 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

Syllabus Jongwook Woo, Ph.D. Office: Simpson Tower, 604 Telephone: #604: (323) 343 - 2916; CIS Office: (323) 343 ‑ 2911 Email: jwoo5@calstatela.edu CIS520 Web Site: http://instructional1.calstatela.edu/jwoo5/classes/2015/spr/bigdata/ Office Hours: Tuesday: 3:40 – 4:20 PM, 6– 8:00 PM Thursday: 4 – 4:20 PM, Friday: 2 – 4:20 PM  ‹#› 2 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

1.Should have NIS account 2.Should have email at CSULA Due date Homework 1 1.Should have NIS account 2.Should have email at CSULA Due date Before the next lab starts at the third week April 10th (Friday) ‹#› 3 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

NIS account Needed How To You need to apply NIS account to logon lab computer at CSULA 10% of HW1 Bring it on the second lab class. How to get MyCSULA account http://www.calstatela.edu/its/helpdesk/gettingstarted http://web.calstatela.edu/library/networkaccount.htm ‹#› 4 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

CSULA Email Account How To In order to communicate with the instructor interactively Email web site how to access https://mymail.calstatela.edu/ Login and password should be the same as NIS account How to forward CSULA email to your personal mail http://www.calstatela.edu/its/docs/pdf/forwarding_emails.pdf http://www.calstatela.edu/its/training/pdf/fwemail.pdf You’d better right-click on the link to download the file instead of left- click on it. ‹#› 5 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

Mastery over MS-Windows File Management (Windows Explorer) facilities. Prerequisites Mastery over MS-Windows File Management (Windows Explorer) facilities. Fundamental Coding / Programming skill Unix (Linux) shell ‹#› 7 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

Course Objectives (Lecture) Identify Big Data that is unstructured data greater than tera-/peta- bytes Learn MapReduce and Data Analytics Learn how to use Amazon AWS.   Learn the fundamental theories and algorithms used to process and store Big Data using MapReduce and Data Analytics See the use cases and examples of Big Data in business ‹#› 8 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

Course Objectives (Lab) With the hands on exercises Setup Hadoop on AWS Practice how to write MapReduce codes Practice MRUnit codes Practice Hive and Data Analysis codes ‹#› 9 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

Related slides, pdf files, papers, web sites etc from the instructor Textbook Instructor’s lecture and lab materials will be posted at a web when the class starts. Related slides, pdf files, papers, web sites etc from the instructor ‹#› 10 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

Expectation for the Course Classroom SH C 344: Friday 10:00 -2:00 PM will be changed to Lab classroom Students are expected to attend every class session For successful completion of Lecture/Lab example, assignments and tests Know how to utilize the equipment or course web site If attendance is not possible, please contact the instructor beforehand to attend other sessions Check out the lab example in one week If you don’t, you wouldn’t catch up the class Not to be late You will have penalties Memory Stick, email Students are expected to use the equipment of computer labs at CSULA for programming or project assignments No excuse not to complete HWs and Lab works for other classes and jobs ‹#› 11 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

Exams and Grading Policy Total: 100% Class Activities (Lab, Attendance, Participation in Lab Class, Not late for Lab Class): 30% 10%: Attendance 20%: Lab Completeness 3 or 4 Homeworks (Questions and Project Assignments): 15% Midterm Exam: 25% Final Term Project Presentation: 30% ‹#› 12 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

Exams and Grading Policy (Cont’d) Tentative Grade At the end of the quarter, you will have a score out of 100 percent. This score will be used in a class curve to arrive at a letter grade. Normally but not guaranteed >= 90 : A (A- or A) >= 80 : B (B-,B,B+) >= 70 : C (C-,C,C+) >=60 : D (D-,D, D+) ‹#› 13 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

Others Use of email A Tentative Course Schedule Email will be used only for short messages and sending attachments of less than one Mega Byte A Tentative Course Schedule See the Syllabus See the Course Website ‹#› 14 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›

Others (Cont’d) Academic dishonesty Giving or Receiving solutions of Homework or Exams The instructor can easily detect the copies F on the assignment or Course Cheating and Plagiarism, etc Normally Individual not Team Assignment See the Course Website ‹#› 15 ‹#› ‹#› ‹#› ‹#› ‹#› ‹#› ‹#›