SPREAD MESSAGE OF INDIAN NATIONAL SECURITY TO AS MANY INDIANS AS POSSIBLE. LET US FREE INDIA OF CORRUPTION BY SPREADING THE MESSAGE TO AS MANY PEOPLE.MANY OF THE ARTICLES HAVE BEEN RECEIVED AS FORWARDED MAIL FROM VARIOUS FRIENDS . SHOULD SOME FACTS BE NOT CORRECT , YOU ARE REQUESTED TO PUT IT IN REMARKS BELOW THE ARTICLE. THIS WILL ENSURE A MORE BALANCED PERSPECTIVE OF THE SUBJECT DISCUSSED.
Saturday, 14 October 2023
Friday, 13 October 2023
Thursday, 12 October 2023
LESSONS FROM HAMAS TERROR ATTACKS FOR INDIA
The problem also lies
in understanding the the capacity and revolutionary speed at which the enemy
mutates itself.
This can be achieved
only when the military minds find themselves in sync with the en’s thought
process. The prerequisite for achieving this stage is - 100% alignment with the
thought of war!
En is meant to
surprise you!
For us too, I feel ,
At Peace - At War should mere be the mental state and not to remain related to
fd- peace postings.
Dynamics and
dimensions of warfare are rapidly changing with the tech changes.
I take it as a good
wake-up call for us as a Nation.
Everything is possible
, plausible in War!
If anything needs to
be learned from this Israeli failure, it is that India needs to be doubly alert
and
all known
terrorist camps should be destroyed. We are surrounded by Islamist terrorists
and China. Enough of appeasement and soft peddling when dealing with known
terrorists and their organisations. Powerful Nation is not restricted to
Economic power but also includes Military power.
*Lessons from Hamas
attack on Israel; Applicable for all nations*
1 If you haven't had a
war for many years, don't assume the enemy has disappeared into thin air,he is
lurking around, looking for your soft belly to hit.
2 Total dependence on
technology is not security, alert foot soldiers on ground are important.
3. If you had no war,
stop thinking soldiers are a drain on your exchequer, they may not be
financially productive but they are assets protectors.
4. Stop tinkering with
the time tested military establishment, no amount of new guns will help,
it is always the man behind the gun who wins war.
5. Pea brain ideas
like Agniveer hit the morale hard, pension of soldiers should not be considered
a wasteful luxury, it is an inescapable requirement, because anyone who signs a
blank cheque of life for the nation should not be considered a load.
6. It is better to
stay protected rather than seeing your expensive assets being blown up as
rubble; you have to pay even to clear the rubble.
7. National Defence is
too serious a matter to be left for the calculative politicians/bureaucracy
(red tape) to handle.
Hamas
Terrorists Attack Israel !
*What led to
this attack ?*
( .... 🥊 Put so cogently ! 👍✊🏾👊✌🏼 _*HIGH TIME THE NATION - CITIZENs
& LEADERs SHED THE BLINKERS😎 !*_
*1.
Complacency* of govt, people, armed forces & Intelligence agencies.
*Priorities
of nation changed* from security & survival to LGBTQ movment, _*divisive
society and local politics !*
2.🚩 *Dependence more on technology* _pushing the priority
of armed forces manpower and policy of boots on grnd_ on to the back burner.
*3.
Political turmoil on local agendas* - changed 4 govt in 2 years.
*4. Ostrich
approach* - all is well..... _give peace a chance_ ......
*❗Lessons for Bhārat.*
1. Do not
try to find peace by peaceful means only !
_You will
get only violence in return._
🥊Lasting *peace is possible only by
being #militarily superior,* *#ever alert and #combat ready*.
2.
Negotiating & *expecting peace with those who have terror in mind* can
prove to be very costly.
_Destroy
terror using all means & if necessary with force_.
That's the
only permanent solution.
*3. Internal
conflict, 🚩🚩🚩🚩🚩political instability,* doubts about
your own policies and *confusion among leaders & upper hierarchy* to suit
political masters 😎🤓🧐, invites disaster.
*4.
Democracy is the only mechanism of governance in modern times.*
But,
_*overdoses of democracy with appeasement of one sect, makes a society weak in
taking clear decisions*_ and determined action.
*5. Don't
talk "Upanishadic" thoughts with an enemy👹 who is ready to behead you.!*
Keep your
hand firmly gripped on a superior weapon and *do not hesitate to👊🤞✌🏼 pre-empt the combat move.*
This
_"No First Attack" / "No First Use" doctrine emboldens the
enemy beyond rationality_…
6.✊🏾 *the Armed forces is your insurance
& guarantee*. _If u take the armed forces as unproductive organization and
find it as burden and costly for your country leading to its cost- cutting_ in
terms of pay, status, pensions and facilities than *one day u will have to pay
many a times higher price and irreparable losses for your country.* ( _should
you give peanuts , one will get only MONKEYs 2 DEFEND the MOTHERLAND!_
*7. Lastly*
remember, its not the machine but the *MAN BEHIND THE MACHINE* who will save
the day and win the wars for the Motherland . *A disgruntled, disappointed and
demoralized DEFENCE FORCES* , due to policies of the govt *is a sure shot
recipe for disaster.* _*Countrymen... time to think & ponder......
Tuesday, 3 October 2023
What are the prerequisites for pursuing a career as a data scientist in India? To pursue a career as a data scientist in India, there are several prerequisites that can enhance your chances of success. Here are some key prerequisites:
What are the prerequisites for pursuing a career as a data
scientist in India?
To pursue a career as a data scientist in India, there are
several prerequisites that can enhance your chances of success. Here are some
key prerequisites:
Education: A strong educational background is essential.
Most data scientist positions require at least a bachelor's degree in a
quantitative field such as computer science, mathematics, statistics,
engineering, or a related discipline. While a bachelor's degree is the minimum
requirement, having a master's or Ph.D. can provide a competitive edge,
especially for more advanced roles.
Programming Skills: Proficiency in programming is crucial
for data scientists. You should have a solid understanding of programming
languages such as Python or R, which are widely used in data science for data
manipulation, analysis, and building machine learning models. Familiarity with
SQL for working with databases is also beneficial.
Statistical Knowledge: Data scientists need a strong foundation
in statistics and probability theory. Understanding concepts such as hypothesis
testing, regression analysis, probability distributions, and statistical
modeling is necessary for extracting insights from data and building accurate
predictive models.
Machine Learning: Data scientists should have a good
understanding of machine learning algorithms and techniques. This includes
knowledge of supervised and unsupervised learning, classification, regression,
clustering, and dimensionality reduction. Familiarity with popular machine
learning libraries and frameworks like scikit-learn, TensorFlow, or PyTorch is
valuable.
Data Wrangling and Visualization: Data scientists spend a
significant amount of time cleaning, preprocessing, and transforming data.
Proficiency in data wrangling techniques, data cleaning, and feature
engineering is essential. Additionally, you should be skilled in data
visualization using tools like Matplotlib, Seaborn, or Tableau to effectively
communicate insights and findings.
Domain Knowledge: Having domain knowledge in the field
you're working in can be advantageous. Understanding the business context and
specific industry challenges can help you extract meaningful insights and
develop relevant data-driven solutions.
Communication and Problem-Solving Skills: Data scientists
need strong communication skills to effectively present their findings,
collaborate with stakeholders, and explain complex concepts to non-technical
audiences. Problem-solving skills are also crucial for identifying data science
challenges, formulating hypotheses, and designing appropriate solutions.
Continuous Learning: The field of data science is
continuously evolving, with new algorithms, tools, and techniques emerging
regularly. Demonstrating a willingness to learn and adapt to new technologies
and methodologies is highly valued.
It's important to note that the specific prerequisites may
vary depending on the company, industry, and level of the data scientist
position you're targeting. Keeping up with the latest trends, participating in
data science competitions, and working on real-world projects can further
strengthen your skills and increase your chances of success as a data scientist
in India.
It's important to note that the specific prerequisites may
vary depending on the company, industry, and level of the data scientist
position you're targeting. Keeping up with the latest trends, participating in
data science competitions, and working on real-world projects can further
strengthen your skills and increase your chances of success as a data scientist
in India.
Here are some additional details related to pursuing a
career as a data scientist in India:
Practical Experience: While having a strong educational
foundation is important, practical experience is highly valued in the field of
data science. Employers often seek candidates who have hands-on experience
working on real-world data science projects. To gain practical experience, you
can participate in Kaggle competitions, work on personal data projects, or seek
internships or entry-level positions in data-related roles.
Specializations: Data science is a broad field, and it can
be beneficial to develop expertise in specific areas or domains. Some popular
specializations within data science include natural language processing (NLP),
computer vision, time series analysis, recommender systems, and deep learning.
Developing skills in these specialized areas can open up niche career
opportunities.
Advanced Mathematics and Algorithms: Data scientists often
encounter complex mathematical concepts and algorithms in their work.
Strengthening your knowledge in areas such as linear algebra, calculus,
optimization, and graph theory can help you understand and implement advanced
machine learning algorithms effectively.
Big Data Technologies: As data volumes continue to grow,
being familiar with big data technologies is advantageous. Learning frameworks
like Apache Hadoop, Spark, and distributed computing concepts can enable you to
work with large-scale datasets efficiently. Knowledge of cloud platforms like
Amazon Web Services (AWS) or Google Cloud Platform (GCP) can also be
beneficial, as many organizations are adopting cloud-based data solutions.
Soft Skills: In addition to technical skills, data
scientists should possess certain soft skills. These include critical thinking,
problem-solving, creativity, and the ability to work in interdisciplinary
teams. Effective communication skills are crucial for presenting complex
findings to stakeholders and collaborating with colleagues across different
domains.
Networking and Professional Development: Building a strong
professional network can be valuable for career growth in data science. Attend
industry conferences, join data science communities, participate in online
forums, and connect with professionals in the field. Engaging in continuous
professional development through workshops, webinars, and online courses can also
help you stay updated with the latest trends and advancements in data science.
Certifications: While not mandatory, certifications can
demonstrate your expertise and commitment to the field. Some popular data
science certifications include the Certified Analytics Professional (CAP),
Microsoft Certified: Azure Data Scientist Associate, and the Data Science
Council of America (DASCA) certifications.
Remember that the field of data science is constantly
evolving, so it's essential to stay updated with the latest technologies,
tools, and methodologies. Continuously learning and expanding your skill set
will provide you with a competitive edge in the job market.
Tell me more.
What are some popular data science communities or online
forums that I can join?
Can you recommend any online courses or workshops for
continuous professional development in data science?
Are there any other certifications that are highly regarded
in the field of data science?
33
CAn you recommend any online courses or workshops for
continuous professional development in data science?
Certainly! There are numerous online courses and workshops
available for continuous professional development in data science. Here are
some popular platforms and resources where you can find quality courses:
Coursera: Coursera offers a wide range of data science
courses from top universities and institutions. Some recommended courses
include "Applied Data Science with Python" from the University of
Michigan, "Machine Learning" by Stanford University, and "Data
Science and Machine Learning Bootcamp with R" by Udemy.
edX: edX is another platform that provides online courses
from renowned universities. You can explore courses like "Data Science and
Machine Learning Bootcamp with Python" from Harvard University,
"Practical Deep Learning for Coders" by fast.ai, and "Data
Science: R Basics" by Harvard University.
Udemy: Udemy offers a vast selection of data science
courses, including both beginner and advanced levels. Courses like "Python
for Data Science and Machine Learning Bootcamp" by Jose Portilla,
"Deep Learning Specialization" by deeplearning.ai, and "Data
Science and Machine Learning Bootcamp with R" by Udemy are highly
regarded.
DataCamp: DataCamp is an online learning platform
specifically focused on data science. It offers interactive courses covering
various topics such as Python, R, SQL, machine learning, and data
visualization. Their courses are hands-on and provide practical coding
experience.
Kaggle: Kaggle is a popular platform for data science
competitions, but it also offers a learning platform called Kaggle Learn. They
provide free courses on topics such as Python, machine learning, deep learning,
and data visualization. The courses often include real-world datasets and
exercises.
LinkedIn Learning: LinkedIn Learning (previously Lynda.com)
offers a comprehensive library of data science courses. You can find courses on
Python for data science, machine learning, statistics, and data visualization.
The courses are taught by industry experts and are often accompanied by
practical exercises.
Google AI Education: Google provides a range of online
resources and courses related to machine learning and data science through its
AI Education platform. The courses cover topics like deep learning, TensorFlow,
and applied machine learning.
Remember to consider your specific learning goals, level of
expertise, and the skills you want to develop when selecting online courses.
Additionally, keep an eye out for free online tutorials, webinars, and
workshops offered by universities, organizations, and industry professionals,
as they can provide valuable insights and updates in the field of data science
Data analytics is indeed a rapidly growing field worldwide, and India is no exception. Information technology professionals with M.Tech degrees have several career options in the realm of data management and analytics.
Data analytics is indeed a rapidly growing field worldwide, and
India is no exception. Information technology professionals with M.Tech degrees
have several career options in the realm of data management and analytics. Here
are some potential career paths and courses that can be pursued for a career in
data management and data analytics in India:
1.
Data Analyst/Data Scientist: These roles involve
extracting, cleaning, and analyzing data to derive valuable insights. Data
scientists often use machine learning and statistical techniques for predictive
modeling. M.Tech graduates can enter these roles with the right skill set in
data analysis, statistics, and programming. Courses in Python, R, SQL, and
machine learning can be beneficial.
2.
Data Engineer: Data engineers are responsible for designing and maintaining
data pipelines and data warehouses. They ensure that data is collected, stored,
and made available for analysis. Skills in databases (SQL, NoSQL), big data
technologies (Hadoop, Spark), and ETL (Extract, Transform, Load) processes are
essential. Courses in these technologies can help.
3.
Business Intelligence (BI) Developer/Analyst: BI professionals
work on tools and platforms like Tableau, Power BI, or QlikView to create
visualizations and reports from data. Knowledge of data modeling, SQL, and
these BI tools is essential.
4.
Big Data Architect: These professionals design and manage the infrastructure for
handling large-scale data processing. Courses in big data technologies like
Hadoop, Spark, and cloud platforms like AWS, Azure, or GCP can be beneficial.
5.
Database Administrator (DBA): DBAs are responsible
for the performance, security, and availability of databases. Specialized
courses in database management systems, security, and optimization can be
helpful.
6.
Data Governance and Compliance Specialist: This role involves
ensuring that data is handled in compliance with regulations (e.g., GDPR) and organizational
policies. Understanding of data governance frameworks and legal aspects is
crucial.
7.
Machine Learning Engineer: For those interested in the
intersection of IT and AI, machine learning engineering involves building and
deploying machine learning models. Courses in machine learning algorithms, deep
learning, and model deployment are essential.
8.
Certifications: Consider obtaining relevant certifications, such as Certified
Data Scientist (CDS), Certified Analytics Professional (CAP), or vendor-specific
certifications like AWS Certified Data Analytics or Microsoft Certified: Azure
Data Scientist.
As for courses specifically focused on big data management in
India, you can explore options such as:
1.
Postgraduate Diploma in Big Data Analytics: Several Indian
universities and institutes offer specialized programs in big data analytics.
2.
Online Courses: Platforms like Coursera, edX, and Udacity offer courses and
specializations in big data technologies, machine learning, and data science.
3.
Certifications: There are various certifications like Cloudera Certified Data
Analyst, Microsoft Certified: Azure Data Engineer, and Google Cloud
Professional Data Engineer that focus on big data and cloud-based analytics.
4.
Training Institutes: Many training institutes and online platforms provide specific
training in Hadoop, Spark, and other big data technologies.
Before choosing a specific career path or course, it's essential
to assess your interests, skills, and career goals. Networking, attending
industry conferences, and staying updated with the latest trends in data
analytics can also be valuable for career growth in this field
33
Data analytics is indeed a rapidly growing field globally,
including in India. With an M.Tech degree in information technology, there are
several career paths you can pursue in data management and analytics. Here are
some options:
Data Scientist: As a data scientist, you will analyze large
datasets, build predictive models, and extract insights to drive business
decisions. You will need strong programming skills, statistical knowledge, and
expertise in machine learning algorithms.
Data Analyst: Data analysts focus on collecting, cleaning,
and interpreting data to uncover patterns and trends. They provide actionable
insights to support business strategies. Proficiency in data visualization,
SQL, and statistical analysis is crucial for this role.
Data Engineer: Data engineers are responsible for designing
and maintaining the infrastructure required for data storage, processing, and
retrieval. They build and optimize data pipelines, ensuring data quality and
integration across systems. Skills in programming, databases, and distributed
computing are essential.
Business Intelligence (BI) Developer: BI developers create
interactive dashboards and reports to visualize data and enable data-driven
decision-making. They work with tools like Tableau, Power BI, or QlikView to
transform complex data into meaningful visualizations.
Big Data Architect: Big data architects design and implement
scalable and distributed systems to handle large volumes of data. They work
with technologies like Hadoop, Spark, and NoSQL databases. Strong knowledge of
distributed computing and data management is required.
In addition to an M.Tech degree, you can consider taking
specialized courses to enhance your skills in big data management and analytics
in India. Some popular courses and certifications include:
Certificate Program in Big Data and Analytics: Offered by
various institutes and online platforms, these programs provide comprehensive
training in big data technologies, analytics, and data management.
Cloudera Certified Data Engineer (CCDE): This certification
validates your skills in designing and building data pipelines, data
transformation, and data storage using Apache Hadoop and related big data
technologies.
SAS Certified Data Scientist: SAS offers a certification
program that covers data manipulation, predictive modeling, machine learning,
and data visualization using SAS tools.
Google Cloud Certified - Data Engineer: This certification
focuses on designing and building data processing systems on the Google Cloud
Platform, including big data solutions like BigQuery and Dataflow.
IBM Certified Data Engineer - Big Data: IBM offers a
certification program that covers big data technologies, including Apache
Hadoop, Spark, and data processing frameworks.
Remember to stay updated with the latest industry trends and
technologies, as the field of data management and analytics continues to evolve
rapidly.
Indian Army turns to ancient texts to prepare for wars of the future
The Indian Army, is embarking on a journey to tap into the rich reservoir of ancient Indian wisdom in statecraft, strategy, diplomacy, and warfare to prepare itself for the challenges of the future. This endeavor, known as "Project Udbhav," represents an initiative by the Army to rediscover India's heritage of statecraft and strategic thought as drawn from ancient Indian texts. In collaboration with the United Service Institution of India (USI), the Army Training Command (ARTRAC) conducted its inaugural hybrid seminar under this project, titled "Evolution of Indian military systems, war-fighting, and strategic thought – current research in the field and way forward." While the project has garnered interest and support, some veterans have raised questions about the applicability of deeprooted Indian strategic concepts in the context of modern and future conflicts. Nonetheless, the Army remains optimistic about Project Udbhav, emphasizing its mission to bridge the historical and the contemporary by delving into India's rich historical narratives in statecraft and strategic thinking. This initiative Agencies aligns with the government's directive to modernize and shed "vestiges of the colonial era" in the armed forces.
Project Udbhav takes a comprehensive approach, encompassing indigenous military systems, historical texts, regional texts and kingdoms, thematic studies, and a focus on the works of ancient strategists like Kautilya. Its aim is not only to rediscover these narratives but also to develop an indigenous strategic vocabulary deeply rooted in India's diverse philosophical and cultural heritage, which can be integrated into modern military education. The project, which began in 2021, has already yielded a book listing 75 aphorisms selected from ancient texts, offering valuable insights into India's strategic heritage. The recent seminar gathered scholars, serving officers, and veterans to study ancient texts dating from the 4th century BC to the 8th century BC, with particular attention to figures like Kautilya, Kamandaka, and The Kural. Project Udbhav will continue with a series of engagements, including the Indian Military Heritage Festival scheduled for October 21-22. The Army's overarching goal is to equip its officers with the ability to apply ancient wisdom to modern scenarios, fostering a deeper understanding of international relations and foreign cultures in the process.