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IMPORTANCE OF AI &
CAREER OPPORTUNITIES
FOR MCA STUDENTS
Venkatarangan Thirumalai
tncv.me | @venkatarangan
3.April.2021
SRM Institute of Science & Technology, Ramapuram
Campus
Agenda
History of A.I.
Areas where A.I. is being
used
Lesser known fields
Well Known Secrets
Major Job Roles in A.I. Major Job Roles in Data
Job Openings Examples
What should I do now?
Options in front of you after
M.C.A.
Life After M.C.A. : Myths
Jobs at risk due to
automation
Next steps after graduating
Last tip!
A Catalan Poet
Ramon Llull in 1308
writes “Ars Generalis
Ultima”
AI is 800
years old
AI Canvas
– Example
for fire
alarm
hbr.org/2018/04/a-simple-tool-to-start-making-decisions-with-the-help-of-ai
Areas where
AI is being
used
1. Banking & Finance
2. E-Commerce
3. Marketing: Online Advertisements, Social Media & more
4. Sales
5. Health Care
6. Communication
Lessor known
areas
1. Military and Defence
2. Construction
3. Agriculture
4. Education
5. Sports
6. Manufacturing
7. Transportation
Well known
secrets
1. Security & Forensic
2. Entertainment
3. Government
Major job
roles in A.I.
1. A.I. Scientist – PhD in Mathematics (algebra, calculus,
algorithms, probability, and statistics), Cognitive Science
Theory, Bayesian Networking (including Neural Nets) &
who can create Algorithms (MIT/Stanford).
2. A.I. Scale Engineer – Top-End Backend/Cloud
Engineer. Knowledge of Programming, Infrastructure &
Storage: HDFS, Apache Spark, Apache Hudi. Work with
highly distributed data. Usage of Algorithms. Identify
bottlenecks in models & regenerate. Develop Model
pipelines.
Major job
roles in Data
3. Data Scientist – Knowledge of Algorithms, Qualified Statistian, Mathematics,
Love for Data, Data Drift & Build models and understand behaviour. Ability to
convert a business problem** to a machine-learning problem.
4. Data Engineer / Data Analyst – Programming Skills, Data Structure &
Formats, Python, SQL, JSON, Apache Avro & Apache Parquet formats, Data
Quality Index & Intro to Statistics
5. Data Labellers – Microsoft Excel, Multiple Data Processing Tools, Jupyter
Notebook, Trillium data quality & Ataccama Data Quality, Apache Spark
6. Data Pipeline Engineer – Analytic Skills, EDL routines, Programming skills,
Data Processing Skills, Data Formats & Visualisation.
WellJobs that
re known
secrets
JOBS THAT
REQUESTS
M.L.
What should I
do now?
1. Choose your Project wisely
2. Internship,
3. Online courses,
4. Github,
5. YouTube videos
Options in
front of you
after MCA
1. Go for higher studies
2. Start on your own
3. Get a job
Life After
MCA:
Myths
1. Job Market is hot, and I have a BE or M.C.A.
2. I must graduate from IIT or a top city college
3. I need to do higher studies to get placed
4. It is for companies to find me and train me
Jobs at
risk due to
Automation
by 2030
mckinsey.com/featured-insights/gender-equality/the-future-of-women-at-work-transitions-in-the-age-of-
automation
Next steps
after
graduating
1. Improve online/offline presentation
2. Attend local industry association events
3. Shortlist companies
4. Don’t wait for advertisements
5. Ask you will get it – Reach out to your network
BOTH!
Business knowledge
or Technical
expertise
Let us continue the conversation
@venkatarangan tncv.me

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Career Opportunities in Artificial Intelligence during the pandemic

  • 1. IMPORTANCE OF AI & CAREER OPPORTUNITIES FOR MCA STUDENTS Venkatarangan Thirumalai tncv.me | @venkatarangan 3.April.2021 SRM Institute of Science & Technology, Ramapuram Campus
  • 2. Agenda History of A.I. Areas where A.I. is being used Lesser known fields Well Known Secrets Major Job Roles in A.I. Major Job Roles in Data Job Openings Examples What should I do now? Options in front of you after M.C.A. Life After M.C.A. : Myths Jobs at risk due to automation Next steps after graduating Last tip!
  • 3. A Catalan Poet Ramon Llull in 1308 writes “Ars Generalis Ultima” AI is 800 years old
  • 4. AI Canvas – Example for fire alarm hbr.org/2018/04/a-simple-tool-to-start-making-decisions-with-the-help-of-ai
  • 5. Areas where AI is being used 1. Banking & Finance 2. E-Commerce 3. Marketing: Online Advertisements, Social Media & more 4. Sales 5. Health Care 6. Communication
  • 6. Lessor known areas 1. Military and Defence 2. Construction 3. Agriculture 4. Education 5. Sports 6. Manufacturing 7. Transportation
  • 7. Well known secrets 1. Security & Forensic 2. Entertainment 3. Government
  • 8. Major job roles in A.I. 1. A.I. Scientist – PhD in Mathematics (algebra, calculus, algorithms, probability, and statistics), Cognitive Science Theory, Bayesian Networking (including Neural Nets) & who can create Algorithms (MIT/Stanford). 2. A.I. Scale Engineer – Top-End Backend/Cloud Engineer. Knowledge of Programming, Infrastructure & Storage: HDFS, Apache Spark, Apache Hudi. Work with highly distributed data. Usage of Algorithms. Identify bottlenecks in models & regenerate. Develop Model pipelines.
  • 9. Major job roles in Data 3. Data Scientist – Knowledge of Algorithms, Qualified Statistian, Mathematics, Love for Data, Data Drift & Build models and understand behaviour. Ability to convert a business problem** to a machine-learning problem. 4. Data Engineer / Data Analyst – Programming Skills, Data Structure & Formats, Python, SQL, JSON, Apache Avro & Apache Parquet formats, Data Quality Index & Intro to Statistics 5. Data Labellers – Microsoft Excel, Multiple Data Processing Tools, Jupyter Notebook, Trillium data quality & Ataccama Data Quality, Apache Spark 6. Data Pipeline Engineer – Analytic Skills, EDL routines, Programming skills, Data Processing Skills, Data Formats & Visualisation.
  • 10.
  • 12.
  • 13.
  • 14. What should I do now? 1. Choose your Project wisely 2. Internship, 3. Online courses, 4. Github, 5. YouTube videos
  • 15. Options in front of you after MCA 1. Go for higher studies 2. Start on your own 3. Get a job
  • 16. Life After MCA: Myths 1. Job Market is hot, and I have a BE or M.C.A. 2. I must graduate from IIT or a top city college 3. I need to do higher studies to get placed 4. It is for companies to find me and train me
  • 17. Jobs at risk due to Automation by 2030 mckinsey.com/featured-insights/gender-equality/the-future-of-women-at-work-transitions-in-the-age-of- automation
  • 18. Next steps after graduating 1. Improve online/offline presentation 2. Attend local industry association events 3. Shortlist companies 4. Don’t wait for advertisements 5. Ask you will get it – Reach out to your network
  • 20.
  • 21. Let us continue the conversation @venkatarangan tncv.me

Editor's Notes

  1. origins of AI, (surprise) it started way back in 1308 when a Catalan Poet & Theologian Ramon Llull publishes his “Ars Generalis Ultima” a paper-based mechanical means to create new knowledge from combinations of concepts.
  2. https://hbr.org/2018/04/a-simple-tool-to-start-making-decisions-with-the-help-of-ai
  3. Refer: https://www.springboard.com/blog/5-careers-in-artificial-intelligence/ Comments for TNCV: AutoML – Data Scientist work will reduce as AutoML. Regenerate Models – Fresh Desk 3000 Models or so, 20 minutes to generate each model, every single day. Identify edge conditions: Tesla should step on a black dot (garbage back) or go around. Driver Decision vs Self driving car. High order affinity for data, unlike affinity for coding/programming languages. No discussion around OO or Function or Similar. Amount of data you handle in AI is more, Code is less. Most sophisticated ML programs are less than 2000 lines of code. These people need to Ensemble Learning: ensemble methods use multiple learning algorithms to obtain better predictive performance. AI & ML – In general, reducing the cost of decision. An AI or ML cannot replace a person with wider skills, it can easily replace a person who is an expert on one skill.
  4. Refer: https://www.springboard.com/blog/5-careers-in-artificial-intelligence/ Comments for TNCV: AutoML – Data Scientist work will reduce as AutoML. Regenerate Models – Fresh Desk 3000 Models or so, 20 minutes to generate each model, every single day. Identify edge conditions: Tesla should step on a black dot (garbage back) or go around. Driver Decision vs Self driving car. High order affinity for data, unlike affinity for coding/programming languages. No discussion around OO or Function or Similar. Amount of data you handle in AI is more, Code is less. Most sophisticated ML programs are less than 2000 lines of code. These people need to Ensemble Learning: ensemble methods use multiple learning algorithms to obtain better predictive performance. AI & ML – In general, reducing the cost of decision. An AI or ML cannot replace a person with wider skills, it can easily replace a person who is an expert on one skill.
  5. Refer: https://www.springboard.com/blog/5-careers-in-artificial-intelligence/ Comments for TNCV: AutoML – Data Scientist work will reduce as AutoML. Regenerate Models – Fresh Desk 3000 Models or so, 20 minutes to generate each model, every single day. Identify edge conditions: Tesla should step on a black dot (garbage back) or go around. Driver Decision vs Self driving car. High order affinity for data, unlike affinity for coding/programming languages. No discussion around OO or Function or Similar. Amount of data you handle in AI is more, Code is less. Most sophisticated ML programs are less than 2000 lines of code. These people need to Ensemble Learning: ensemble methods use multiple learning algorithms to obtain better predictive performance. AI & ML – In general, reducing the cost of decision. An AI or ML cannot replace a person with wider skills, it can easily replace a person who is an expert on one skill.
  6. Refer: https://www.springboard.com/blog/5-careers-in-artificial-intelligence/ https://medium.com/@albertchristopherr/how-to-start-a-career-in-artificial-intelligence-in-2019-a-step-by-step-guide-b18ad32d1b1f Comments for TNCV: AutoML – Data Scientist work will reduce as AutoML. Regenerate Models – Fresh Desk 3000 Models or so, 20 minutes to generate each model, every single day. Identify edge conditions: Tesla should step on a black dot (garbage back) or go around. Driver Decision vs Self driving car. High order affinity for data, unlike affinity for coding/programming languages. No discussion around OO or Function or Similar. Amount of data you handle in AI is more, Code is less. Most sophisticated ML programs are less than 2000 lines of code. These people need to Ensemble Learning: ensemble methods use multiple learning algorithms to obtain better predictive performance. AI & ML – In general, reducing the cost of decision. An AI or ML cannot replace a person with wider skills, it can easily replace a person who is an expert on one skill.
  7. Refer: https://www.springboard.com/blog/5-careers-in-artificial-intelligence/ Comments for TNCV: AutoML – Data Scientist work will reduce as AutoML. Regenerate Models – Fresh Desk 3000 Models or so, 20 minutes to generate each model, every single day. Identify edge conditions: Tesla should step on a black dot (garbage back) or go around. Driver Decision vs Self driving car. High order affinity for data, unlike affinity for coding/programming languages. No discussion around OO or Function or Similar. Amount of data you handle in AI is more, Code is less. Most sophisticated ML programs are less than 2000 lines of code. These people need to Ensemble Learning: ensemble methods use multiple learning algorithms to obtain better predictive performance. AI & ML – In general, reducing the cost of decision. An AI or ML cannot replace a person with wider skills, it can easily replace a person who is an expert on one skill.
  8. Refer: https://www.springboard.com/blog/5-careers-in-artificial-intelligence/ https://medium.com/@albertchristopherr/how-to-start-a-career-in-artificial-intelligence-in-2019-a-step-by-step-guide-b18ad32d1b1f Comments for TNCV: AutoML – Data Scientist work will reduce as AutoML. Regenerate Models – Fresh Desk 3000 Models or so, 20 minutes to generate each model, every single day. Identify edge conditions: Tesla should step on a black dot (garbage back) or go around. Driver Decision vs Self driving car. High order affinity for data, unlike affinity for coding/programming languages. No discussion around OO or Function or Similar. Amount of data you handle in AI is more, Code is less. Most sophisticated ML programs are less than 2000 lines of code. These people need to Ensemble Learning: ensemble methods use multiple learning algorithms to obtain better predictive performance. AI & ML – In general, reducing the cost of decision. An AI or ML cannot replace a person with wider skills, it can easily replace a person who is an expert on one skill.
  9. Refer: https://www.springboard.com/blog/5-careers-in-artificial-intelligence/ https://medium.com/@albertchristopherr/how-to-start-a-career-in-artificial-intelligence-in-2019-a-step-by-step-guide-b18ad32d1b1f Comments for TNCV: AutoML – Data Scientist work will reduce as AutoML. Regenerate Models – Fresh Desk 3000 Models or so, 20 minutes to generate each model, every single day. Identify edge conditions: Tesla should step on a black dot (garbage back) or go around. Driver Decision vs Self driving car. High order affinity for data, unlike affinity for coding/programming languages. No discussion around OO or Function or Similar. Amount of data you handle in AI is more, Code is less. Most sophisticated ML programs are less than 2000 lines of code. These people need to Ensemble Learning: ensemble methods use multiple learning algorithms to obtain better predictive performance. AI & ML – In general, reducing the cost of decision. An AI or ML cannot replace a person with wider skills, it can easily replace a person who is an expert on one skill.
  10. Refer: https://www.springboard.com/blog/5-careers-in-artificial-intelligence/ https://medium.com/@albertchristopherr/how-to-start-a-career-in-artificial-intelligence-in-2019-a-step-by-step-guide-b18ad32d1b1f Comments for TNCV: AutoML – Data Scientist work will reduce as AutoML. Regenerate Models – Fresh Desk 3000 Models or so, 20 minutes to generate each model, every single day. Identify edge conditions: Tesla should step on a black dot (garbage back) or go around. Driver Decision vs Self driving car. High order affinity for data, unlike affinity for coding/programming languages. No discussion around OO or Function or Similar. Amount of data you handle in AI is more, Code is less. Most sophisticated ML programs are less than 2000 lines of code. These people need to Ensemble Learning: ensemble methods use multiple learning algorithms to obtain better predictive performance. AI & ML – In general, reducing the cost of decision. An AI or ML cannot replace a person with wider skills, it can easily replace a person who is an expert on one skill.
  11. Refer: https://www.springboard.com/blog/5-careers-in-artificial-intelligence/ https://medium.com/@albertchristopherr/how-to-start-a-career-in-artificial-intelligence-in-2019-a-step-by-step-guide-b18ad32d1b1f Comments for TNCV: AutoML – Data Scientist work will reduce as AutoML. Regenerate Models – Fresh Desk 3000 Models or so, 20 minutes to generate each model, every single day. Identify edge conditions: Tesla should step on a black dot (garbage back) or go around. Driver Decision vs Self driving car. High order affinity for data, unlike affinity for coding/programming languages. No discussion around OO or Function or Similar. Amount of data you handle in AI is more, Code is less. Most sophisticated ML programs are less than 2000 lines of code. These people need to Ensemble Learning: ensemble methods use multiple learning algorithms to obtain better predictive performance. AI & ML – In general, reducing the cost of decision. An AI or ML cannot replace a person with wider skills, it can easily replace a person who is an expert on one skill.