Current IT skills in high demand include software development, web development, networking, and other technical roles. The global IT industry is growing rapidly, especially in India where the IT sector generates billions in revenue and employs millions of people. Technical skills like programming, databases, and software engineering are in high demand. However, employers also value soft skills like problem solving, communication, and teamwork. To be successful, one needs both strong technical abilities and soft skills. Puzzles, logic games, and stories from works like the Panchatantra and Mahabharata can help develop the critical thinking and reasoning skills valued by employers.
Lean Analytics is a set of rules to make data science more streamlined and productive. It touches on many aspects of what a data scientist should be and how a data science project should be defined to be successful. During this presentation Richard will present where data science projects go wrong, how you should think of data science projects, what constitutes success in data science and how you can measure progress. This session will be loaded with terms, stories and descriptions of project successes and failures. If you're wondering whether you're getting value out of data science, how to get more value out of it and even whether you need it then this talk is for you!
What you will take away from this session
Learn how to make your data science projects successful
Evaluate how to track progress and report on the efficacy of data science solutions
Understand the role of engineering and data scientists
Understand your options for processes and software
Board Infinity Data Science Brochure - data science learning pathBoard Infinity
Join our Data Science Course to become a Certified Data Scientist! Master in the highly demanded technologies like SQL, Python alongside the concepts of Data Exploration, Regression Models, Hypothesis Testing. Get 1:1 personal coaching and mentoring straight from Top Data Science Coaches to be job-ready. This includes the complete data science syllabus, project, hackathons, and Data Science Certification.
In this presentation, Microsoft data scientists Ben Keen and Shahzia Holtom cover an introduction to data science with respect to:
- What is a data scientist?
- What data does a data scientist need?
- AI ethics and responsibility
- What is MLOps and how does it drive value?
Brochure data science learning path board-infinity (1)NirupamNishant2
Board Infinity is a best digital marketing and data science institute in mumbai, which is a full-stack career platform for students and jobseekers enabled by personalised learning paths,career coaches and access to various job oppurtunities. We provide online and offline training in Data Science, Digital Marketing, Full stack Web Development,Product management< machine learning and Atrificial Intelligence,Online career counselling and other career solutions
Overview of a Machine Learning 11 week course I developed and trained software engineers at Dell on their way to become Data Scientists. Class is outline of Predictive Analytics methods using Python. I taught this class 8 separate occasions over 3 years.
Lean Analytics is a set of rules to make data science more streamlined and productive. It touches on many aspects of what a data scientist should be and how a data science project should be defined to be successful. During this presentation Richard will present where data science projects go wrong, how you should think of data science projects, what constitutes success in data science and how you can measure progress. This session will be loaded with terms, stories and descriptions of project successes and failures. If you're wondering whether you're getting value out of data science, how to get more value out of it and even whether you need it then this talk is for you!
What you will take away from this session
Learn how to make your data science projects successful
Evaluate how to track progress and report on the efficacy of data science solutions
Understand the role of engineering and data scientists
Understand your options for processes and software
Board Infinity Data Science Brochure - data science learning pathBoard Infinity
Join our Data Science Course to become a Certified Data Scientist! Master in the highly demanded technologies like SQL, Python alongside the concepts of Data Exploration, Regression Models, Hypothesis Testing. Get 1:1 personal coaching and mentoring straight from Top Data Science Coaches to be job-ready. This includes the complete data science syllabus, project, hackathons, and Data Science Certification.
In this presentation, Microsoft data scientists Ben Keen and Shahzia Holtom cover an introduction to data science with respect to:
- What is a data scientist?
- What data does a data scientist need?
- AI ethics and responsibility
- What is MLOps and how does it drive value?
Brochure data science learning path board-infinity (1)NirupamNishant2
Board Infinity is a best digital marketing and data science institute in mumbai, which is a full-stack career platform for students and jobseekers enabled by personalised learning paths,career coaches and access to various job oppurtunities. We provide online and offline training in Data Science, Digital Marketing, Full stack Web Development,Product management< machine learning and Atrificial Intelligence,Online career counselling and other career solutions
Overview of a Machine Learning 11 week course I developed and trained software engineers at Dell on their way to become Data Scientists. Class is outline of Predictive Analytics methods using Python. I taught this class 8 separate occasions over 3 years.
Data Workflows for Machine Learning - Seattle DAMLPaco Nathan
First public meetup at Twitter Seattle, for Seattle DAML:
http://www.meetup.com/Seattle-DAML/events/159043422/
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How to crack Big Data and Data Science rolesUpXAcademy
How to crack Big Data and Data Science roles is the flagship event of UpX Academy. This slide was used for the event on 10th Sept that was attended by hundreds of participants globally.
Digicrome Data Science & AI 11 Month Course PDF.pdfitsmeankitkhan
Dive into the world of Artificial Intelligence and Data Science with Digicrome's dynamic Postgraduate Program (PGP). Our uniquely crafted curriculum blends theory with hands-on projects, led by industry experts. From cutting-edge algorithms to practical applications Artificial Intelligence Certification, elevate your skills and career prospects in today's data-driven landscape.
If there is one crucial thing in building ML models, this would be the data preparation. That is the process of transforming raw data to a state where machine learning algorithms could be run to disclose insights and make predictions. Data preparation involves analysis, depends on the nature of the problem and the particular algorithms. As far as there are knowledge and experience involved, there is no such thing as automation, which makes the role of the data scientist the key to success.
ML is trendy and Microsoft already have more than 10 services to support ML. So we will focus on tools like Azure ML Workbench and Python for data preparation, review some common tricks to approach data and experiment in Azure ML Studio.
How to Become a Data Scientist
SF Data Science Meetup, June 30, 2014
Video of this talk is available here: https://www.youtube.com/watch?v=c52IOlnPw08
More information at: http://www.zipfianacademy.com
Zipfian Academy @ Crowdflower
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My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Data Workflows for Machine Learning - Seattle DAMLPaco Nathan
First public meetup at Twitter Seattle, for Seattle DAML:
http://www.meetup.com/Seattle-DAML/events/159043422/
We compare/contrast several open source frameworks which have emerged for Machine Learning workflows, including KNIME, IPython Notebook and related Py libraries, Cascading, Cascalog, Scalding, Summingbird, Spark/MLbase, MBrace on .NET, etc. The analysis develops several points for "best of breed" and what features would be great to see across the board for many frameworks... leading up to a "scorecard" to help evaluate different alternatives. We also review the PMML standard for migrating predictive models, e.g., from SAS to Hadoop.
How to crack Big Data and Data Science rolesUpXAcademy
How to crack Big Data and Data Science roles is the flagship event of UpX Academy. This slide was used for the event on 10th Sept that was attended by hundreds of participants globally.
Digicrome Data Science & AI 11 Month Course PDF.pdfitsmeankitkhan
Dive into the world of Artificial Intelligence and Data Science with Digicrome's dynamic Postgraduate Program (PGP). Our uniquely crafted curriculum blends theory with hands-on projects, led by industry experts. From cutting-edge algorithms to practical applications Artificial Intelligence Certification, elevate your skills and career prospects in today's data-driven landscape.
If there is one crucial thing in building ML models, this would be the data preparation. That is the process of transforming raw data to a state where machine learning algorithms could be run to disclose insights and make predictions. Data preparation involves analysis, depends on the nature of the problem and the particular algorithms. As far as there are knowledge and experience involved, there is no such thing as automation, which makes the role of the data scientist the key to success.
ML is trendy and Microsoft already have more than 10 services to support ML. So we will focus on tools like Azure ML Workbench and Python for data preparation, review some common tricks to approach data and experiment in Azure ML Studio.
How to Become a Data Scientist
SF Data Science Meetup, June 30, 2014
Video of this talk is available here: https://www.youtube.com/watch?v=c52IOlnPw08
More information at: http://www.zipfianacademy.com
Zipfian Academy @ Crowdflower
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
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Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
6. India: The Knowledge-based Civilization
• World’s first knowledge-based civilization since the Vedic
times, 5000 years back
• Veda = Knowledge
• Vast knowledge heritage through the centuries
• First universities (Takshashila, Nalanda) were borne here
• Invention of zero, decimal system, and early advances in
language, mathematics, astronomy, etc. credited to India.
• Richest country of the world till the 11th century
• In the 20th century, India was termed as a rich country where
poor people live
7. Indian IT Scenario
• IT- BPO sector estimated revenues of USD 88.1billion in 2011
• IT software & services about USD 76.1 billion
• Employment –about 2.5 million
• Indirect job creation –about 8.3 million
• Contribution to GDP -6.4% from 1.2% in 1998
• Exports -26% of total exports from less than 4% in 1998
• Export revenues (including Hardware) estimated to reach USD
59.4 billion in FY2011
• Domestic revenues (including Hardware) of about USD 28.8
billion
• By 2015, Indian IT-BPO sector can generate revenues of USD
130 billion
(source – NASSCOM)
8. ITeS/BPO
• A form of outsourced service which has emerged due
to involvement of IT in various fields such as banking
and finance, telecommunications, insurance, etc.
• Mostly back-office processing outsourced to India
• Call-centre operations
• No need of high technical skills
• Any graduate, PUC or Diploma will do
• 24x7 working conditions
9. Information Technology
• The
study, design, development, implementation, suppor
t or management of computer-based information
systems, particularly software applications and
computer hardware
• Jobs for technically qualified only
• BE, BTech, MTech, MCA,
Also MSc(CS), BSc(CS), BCA
10. IT job opportunities
• Software development
• Web development
• IT Professional (includes Networking specialist)
• Graphics/Multimedia/Creative
• CAD/CAM
• DB Analyst, DB Architect, Datawarehousing, Datamining
• Game development
• Software Testing & Quality Assurance
• Embedded development
• ERP
• Internationalization/Localization
• Security specialist
• Technical writing & Documentation specialist
• Help desk & Technical support
12. Position Position Programming Ratings Delta
Top 20 Programming Languages 2012
Jan 2012 Jan 2011 Language Jan 2012 Jan 2011
1 1 Java 17.479% -0.29%
2 2 C 16.976% +1.15%
3 6 C# 8.781% +2.55%
4 3 C++ 8.063% -0.72%
5 8 Objective-C 6.919% +3.91%
6 4 PHP 5.710% -2.13%
7 7 (Visual) Basic 4.531% -1.34%
8 5 Python 3.218% -3.05%
9 9 Perl 2.773% -0.08%
10 11 JavaScript 2.322% +0.73%
Delphi/Object
11 12 1.576% +0.29%
Pascal
12 10 Ruby 1.441% -0.34%
13 13 Lisp 1.111% +0.00%
14 14 Pascal 0.798% -0.12%
15 17 Transact-SQL 0.772% +0.01%
16 24 PL/SQL 0.709% +0.15%
17 20 Ada 0.634% -0.05%
18 39 Logo 0.632% +0.29%
19 25 R 0.609% +0.07%
20 21 Lua 0.559% -0.08% 12
13. Top 10 Qualities Employers Want
• Honesty / Integrity
• Analytical Skills
• Strong Work Ethic
• Motivation / Initiative
• Communication Skills (Verbal and Written)
• Interpersonal Skills (relate well to others)
• Teamwork Skills (work well with others)
• Flexibility / Adaptability
• Computer Skills
• Detail Oriented
14. What it takes to be a great
programmer?
• An engineering degree with high percentage like BE
(CS), Btech (CS), MCA, MTech, MSc (CS),.. ?
• A great score in any degree mentioned above?
• A great communication skill?
15. Landing an IT job
• Certificates alone can’t get the job
• Knowledge is important
• How to apply the knowledge and solve a problem is
the key to get a job
• Learning ability –learn from problems faced and take
the solutions to new problems
• Industry does not need walking encyclopedias
• Industry wants problem solvers
16. To become a software pro…
Should possess these -
• Logical reasoning ability
• Numerical ability
• Imaginative mind
• Interest in problem-solving
• Interest in keeping oneself updated about new
technology
• Communication skills, written and oral, is a plus point
17. Aptitude
• Bill Gates:
– IQ is all that matters
– I could teach a smart person anything
• Lewis M Terman:
– Definition of intelligence -the ability to reason abstractly
– Intelligence is not knowledge of facts but the ability to manipulate
concepts
• A company will be only as creative and innovative as
the people it hires
• Golden rule: hire for aptitude & attitude and train on
skills
19. Sample numerical questions
1. In a class composed of x girls and y boys what part
of the class is composed of girls?
A. y/(x + y) B. x/xy C. x/(x + y) D. y/xy
2. If a person drives at average speed of 40kmph from
A to B and at average speed of 60kmph from B to
A, what is the total average speed for the trip?
A. 50 B. 100 C. 48 D. 24
20. Sample Logical Reasoning and
Analytical Skills Question
1. Pick one symbol from the options to continue the sequence
A B C D E
2. A is the widow of B. B & C were the only children of E. C is
unmarried and is a doctor. D is the granddaughter of E and
studies science. How is D related to A?
A. Aunt B. Daughter D. Sister D. Sister-in-law
21. Importance of Puzzles
• Bill Gates is known to be fond of puzzles
• Microsoft, Google, ThoughtWorks and many companies
hire people who solve puzzles
• Solving puzzles help in improving logical reasoning and
analytical skills
• Books are there in market based on these puzzles
22. Sample Puzzles -1
1. You have 9 balls which look alike in color, shape and size.
Out of them 8 are equal in weight also but one is heavier.
You have been given a balance but no weights. How will
you find out the heavier ball in two weighings?
2. Why are the manhole lids are in circular shape?
3. You have mugs of 3 liter and 5 liter capacity. There is a big
bucket with water. How can you measure exactly 4 liter of
water?
23. Sample Puzzles -2
4. There are 5 jars filled with pills. All pills are supposed to be
of 10 gm weight. The jars are numbered 1, 2, ..5. One of
them has pills of 9 gm. You are given an electronic
balance. By using the balance only once, you have to find
out the contaminated jar.
5. You have an employee who has to be paid by 1” long gold
bar as salary for every day. You have a gold bar of 7” long
with 1” markings. You are allowed to make just 2 cuts in
the bar. You have to settle the salary every day. How do
you achieve this?
24. Sample Puzzles -3
6. Three persons are standing in a straight line. You have 3
red hats and 2 black hats. You put one hat on each
person’s head at random and put the remaining hats away.
No one has seen the colors of those hats. You first ask the
last person what is color of the hat on his head. He says he
can't know. Then you ask the same question to the person
in the middle. He also says he can’t. The you ask the same
question to the person who is in the beginning. He gives
the correct answer . What was the color of hat on his
head?
25. Books one can read
How Would You Move Mount Fuji?
Microsoft's Cult of the Puzzle
By William Poundstone
Puzzles For Programmers And Pros
By Dennis E. Shasha
How to Solve It by Computer
By R. G. Dromey
Algorithms + Data Structures = Programs
By Niklaus Wirth
26. Program & Efficient Program
• Finding GCD of 2 numbers-
Algorithm-1 Algorithm-2
function gcd(a, b) function gcd(a, b)
if a = 0 while b ≠ 0
return b t := b
while b ≠ 0 b := a mod b
if a > b a := t
a := a − b return a
else
b := b − a
return a
Which is faster?
27. Panchatantra
• Stories for children
– Converting fools to wise by telling thought provoking stories
• Five main sections-
– Mitra-bheda: The Separation of Friends (The Lion and the Bull)
– Mitra-lābha or Mitra-samprāpti: The Gaining of Friends (The
Dove, Crow, Mouse, Tortoise and Deer)
– Kākolūkīyam: Of Crows and Owls (War and Peace)
– Labdhapraṇāśam: Loss Of Gains (The Monkey and the Crocodile)
– Aparīkṣitakārakaṃ: Ill-Considered Action / Rash deeds (The Brahman
and the Mongoose)
• Contains principles of nīti - the wise conduct of life
• Complete knowhow to logic as well as moral science
to everyone
28. Mahabharata
• Indians are deep rooted in Mahabharata
• Mahabharata contains essence of life
• Everything need to live a good life is there in
Mahabharata
• Mahabharata contains Gita
• Mahabharata and Gita have lessons on
teamwork, leadership, management, etc.
• Most important for software professionals –
– Mahabharata is full of logic
29. Examples of Logic in Mahabharata
• Stories in adiparva like Hiranyakashipu and Prahlada
• War between Sudhanva and Arjuna –the 2 oaths and
Krishna’s dilemma
• Draupadi’s question
• How Damayanti identifies real Nala
…..many more
30. FAQ
• What makes a student employable?
– Thinking & Learning ability
• Do communication and team skills put students from
rural colleges at a disadvantage?
– No
• Does high percentage in college exam leads to getting
job?
– No. Scoring well in the aptitude test is most important
• Can certifications like Microsoft, CCNA, Java get jobs?
– Not necessarily, but they will increase the possibility
31. Lifelong learning
• You are the owner of your career
• A new college graduate starting their first job has just
begun to learn
• If you do not learn and grow you will be left behind
• Job security does not exist
• Employability security exists for people who have the
skills and knowledge that are in demand
32. Conclusions
• To be a great programmer
– one must have good logical reasoning and analytical skills
• To achieve these
– Solve puzzles
– Read Mahabharata
– Play Chess
34. Contact
Dr. Pavanaja U. B.
pavanaja@vishvakannada.com
www.pavanaja.com
www.vishvakannada.com
www.linkedin.com/in/pavanaja
www.twitter.com/pavanaja
www.facebook.com/pavanaja
ganakindi.blogspot.com
34
Lewis Madison Terman (15 January 1877 in Johnson County, Indiana – 21 December 1956 in Palo Alto, California) was an Americanpsychologist, noted as a pioneer in educational psychology in the early 20th century at the Stanford University School of Education. He is best known as the inventor of the Stanford-Binet IQ test.
Tailpiece (humor) – How many kauravas were there? (use of digital computing)