Data Science Fundamentals for IT Professionals - (Live Global Webinar)

When:  Apr 29, 2023 from 09:00 to 17:00 (ET)
Associated with  New York Metropolitan Chapter

The final class registration day will be closed on April 24th 2023 at 8 pm. No exceptions are made.

Discounted member rates apply to any chapter member in the world.

Note:  Due to COVID-19 This event will be online only " Please register for this class using the private email address (Gmail, yahoo, AOL, Hotmail address) and not your organizations' email address.
Many organizations block emails with attachments and block Webex links"


Dates and Times: All times are New York time (Eastern Standard Time). Please click here to hear the time and date in your location.

Saturday, April 29, 2022  9:00 AM – 5:00 PM EST 

Prerequisite: Some experience in IT  or IT Audit 

Instructor: Jay Ranade, CISA, CISM, CRISC, CGEIT, CIA, CRMA, CISSP, ISSAP, CBCP, CDPSE, HCISPP

Who Should Attend?

Training Duration: 1 day
Training Delivery Method: On-line during the pandemic

Course Material:
Content-rich handouts with 127 slides from Jay Ranade.

COURSE DESCRIPTION:

Here is what will be covered:

1. What is data science? Study of data to extract meaningful insights for business.
2. Data science, data engineer, Business Analytics, Predictive analytics, Big Data
3. Statistics, Visualization, Deep Learning, Machine Learning
4. Skills of data scientist- Statistical analysis and computing: Machine Learning. Deep Learning, Processing large data sets, Data Visualization, Data Wrangling, Mathematics, Programming Python, R etc)
5. Job: researching, writing algorithms and writing code to answer the questions about the data sets in question
6. Five Vs of analytics vs. 5 Ps of data science- The 5 Ps of product, price, promotion, place, and people
7. Do you register for college degree or certification? Can you learn on your own?
8. 4 Types of Data: Nominal, Ordinal, Discrete, Continuous  
9. Big Data vs. Data science vs data engineering vs data analytics vs. AI vs. ML vs. DL
10. Big Data – past, present and predictive
11. Six things will help – Apache Hadoop, Python, R, data mining, SQL, data structures
12. Types of analytics- diagnostic, descriptive, prescriptive, and predictive analytics
13. Low cost learning/certificate of data analytics-



CPE Credits: 7     Capacity: webinar - 12 people

Onsite Location: N/A

Live broadcast webinar location: Anywhere in the world

Very Important:

Onsite Location: N/A

Live broadcast webinar location: Anywhere in the world
Refund Policy: 80% refund on or before March 29, 2023. A refund must be requested in writing and will not be accepted after the said date. Cancellation/refund requests will not be awarded once class materials have been sent to the registrants. Anyone who has received the class materials will be required to pay the class fee in full.  Failures of payment will be banned from all chapter event until the outstanding balance are clear.

Very Important:
Anyone who fails to make a payment online will not be considered an attendee.  Anyone who has received the class materials will be required to pay the class fee in full.  Failures of payment will be banned from all chapter event until the outstanding balance are clear.


  • CPE  credits can be applied toward each ISACA designation that is held. Full  CPE credits will be awarded only if all sections of Exam Preparation classes have been attended.
  • Webinar sessions are not being recorded - it's a live broadcast.
  • You cannot switch between onsite and online sessions once decided.
  • Webinar access instructions are provided 5 days prior to the first day of class.
  • For webinar attendees, you can also test if you are able to connect to the gotowebinar website by following the instructions here: http://bit.ly/1JvcdSy