Want to pursue career in Data Science? Have knowledge of limited opportunities? Don't worry!
This e- book helps readers to know about top career opportunities one can pursue in Data Science. Further info.- https://www.henryharvin.com/business-analytics-course-with-python
Attend The Data Science Course in Bangalore From ExcelR. Practical Data Science Course in Bangalore Sessions With Assured Placement Support From Experienced Faculty. ExcelR Offers The Data Science Course in Bangalore.
Data scientists and IT push the limits of what's possible -- whether that's operating more efficiently, taking advantage of new opportunities, or innovating. Here are 5 ways businesses can boost their effectiveness.
For more: http://blog.tyronesystems.com/
Data science is different from Data Analytics,Data Engineering,Big Data.
Presentation about Data Science.
What is Data Science its process future and scope.
Data Science Presentation By Amit Singh.
"Sexiest job of 21st century"
Data Science is the Sexiest job in 21st century. Big Data Concept is going to rule the 21st century. Here is the presentation to give complete information and overview of data science big data.
This video includes:
Purpose of Data Science, Role of Data Scientist, Skills required for Data Scientist, Job roles for Data Scientist, Applications of Data Science, Career in Data Science.
Attend The Data Science Course in Bangalore From ExcelR. Practical Data Science Course in Bangalore Sessions With Assured Placement Support From Experienced Faculty. ExcelR Offers The Data Science Course in Bangalore.
Data scientists and IT push the limits of what's possible -- whether that's operating more efficiently, taking advantage of new opportunities, or innovating. Here are 5 ways businesses can boost their effectiveness.
For more: http://blog.tyronesystems.com/
Data science is different from Data Analytics,Data Engineering,Big Data.
Presentation about Data Science.
What is Data Science its process future and scope.
Data Science Presentation By Amit Singh.
"Sexiest job of 21st century"
Data Science is the Sexiest job in 21st century. Big Data Concept is going to rule the 21st century. Here is the presentation to give complete information and overview of data science big data.
This video includes:
Purpose of Data Science, Role of Data Scientist, Skills required for Data Scientist, Job roles for Data Scientist, Applications of Data Science, Career in Data Science.
Data Science is a form of science that focuses on dealing with huge chunks of data by using modern data analysis tools and techniques to discover hidden patterns, meaningful insights, and make critical business decisions.
A Data Science professional has to utilize complicated machine learning algorithms to develop predictive models. There could be multiple sources present in different formats used in data analysis.
Data Science is a new technology, which is basically used for apply critical analysis. It utilizes the potential and scope of Hadoop. It also helps fully in R programming and machine learning implementation. It is a blend of multiple technologies like data interface, algorithm. It helps to solve an analytical problem. Data Science provides a clear understanding of work in big data, analytical tool R. Also, it provide the analyses of big data. It gives a clear idea of understanding of data, transforming the data. Also, it helps in visualizing the data, exploratory analysis, understanding of null value. It used to impute the value with the help of different rules and logic.
Do you want to understand the emerging new data-driven jobs? This presentation discusses the emerging roles of Data Science and Data Engineering, and how they are related to Business Intelligence and Big Data. We will talk about skills and background needed for the jobs, and what education and certification is important.
Defining Data Science
• What Does a Data Science Professional Do?
• Data Science in Business
• Use Cases for Data Science
• Installation of R and R studio
Data science and visualization lab presentationiHub Research
The Data Science and Visualization Lab! This product is based on a component of research that delves into and innovates on the processes of data science – collection, storage/management, analysis and visualization. You have probably come across one of our amazing info-graphics. What else can you do with data?
Data Science Applications | Data Science For Beginners | Data Science Trainin...Edureka!
** Data Science Certification using R: https://www.edureka.co/data-science **
This Edureka "Data Science Applications" PPT takes you through the various domains in which data science is being deployed today, along with some potential applications of this technology. The world today runs on data and this PPT shows exactly that.
Check out our Data Science Tutorial blog series: http://bit.ly/data-science-blogs
Check out our complete Youtube playlist here: http://bit.ly/data-science-playlist
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Explains: What is Data Science? What is the difference between Data Science and Data Engineering, and between Data Science and Business Intelligence? What type of work do Data Scientists do, and what types of companies employ them? What is the job outlook for Data Science? What professional education is required?
In this presentation, I have talked about Big Data and its importance in brief. I have included the very basics of Data Science and its importance in the present day, through a case study. You can also get an idea about who a data scientist is and what all tasks he performs. A few applications of data science have been illustrated in the end.
FUTURE OF DATA SCIENCE IN INDIA
DATA SCIENCE
It is a tool that uses all kinds of data, algorithms and scientific methods. It is a very important tool as it combines two of the most important things in technology and modern science that is mathematics and computer science together. Organizing, data delivery and packaging are the three most important components involved in data science. Data Science handles data works on them and makes conclusion based on the data.
Understand the Demand of Analyst Opportunity in U.SJiaming Zhang
The slides summarize an analysis on the demand pattern of analyst opportunity (like data analyst, data science) in the U.S.
In a nutshell, it answer four questions, including the demand trend, demand source, degree and skill requirement based on the online job posting data.
This was first part of the presentation on "Road Map for Careers in Big Data" in Conjunction with Hortonworks/Aengus Rooney on 17th August 2016 in London. For those contemplating moving to Big Data from often Relational Background
Data Analytics with R, Contents and Course materials, PPT contents. Developed by K K Singh, RGUKT Nuzvid.
Contents:
Introduction to Data, Information and Data Analytics,
Types of Variables,
Types of Analytics
Life cycle of data analytics.
A Seminar Presentation on Big Data for Students.
Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. This type of data requires a different processing approach called big data, which uses massive parallelism on readily-available hardware.
In this presentation, let's have a look at What is Data Science and it's applications. We discussed most common use cases of Data Science.
I presented this at LSPE-IN meetup happened on 10th March 2018 at Walmart Global Technology Services.
Being able to make data driven decisions is a crucial skill for any company. The requirements are growing tougher - the volume of collected data keeps increasing in orders of magnitude and the insights must be smarter and faster. Come learn more about why data science is important and what challenges the data teams need to face.
Data Science is a form of science that focuses on dealing with huge chunks of data by using modern data analysis tools and techniques to discover hidden patterns, meaningful insights, and make critical business decisions.
A Data Science professional has to utilize complicated machine learning algorithms to develop predictive models. There could be multiple sources present in different formats used in data analysis.
Data Science is a new technology, which is basically used for apply critical analysis. It utilizes the potential and scope of Hadoop. It also helps fully in R programming and machine learning implementation. It is a blend of multiple technologies like data interface, algorithm. It helps to solve an analytical problem. Data Science provides a clear understanding of work in big data, analytical tool R. Also, it provide the analyses of big data. It gives a clear idea of understanding of data, transforming the data. Also, it helps in visualizing the data, exploratory analysis, understanding of null value. It used to impute the value with the help of different rules and logic.
Do you want to understand the emerging new data-driven jobs? This presentation discusses the emerging roles of Data Science and Data Engineering, and how they are related to Business Intelligence and Big Data. We will talk about skills and background needed for the jobs, and what education and certification is important.
Defining Data Science
• What Does a Data Science Professional Do?
• Data Science in Business
• Use Cases for Data Science
• Installation of R and R studio
Data science and visualization lab presentationiHub Research
The Data Science and Visualization Lab! This product is based on a component of research that delves into and innovates on the processes of data science – collection, storage/management, analysis and visualization. You have probably come across one of our amazing info-graphics. What else can you do with data?
Data Science Applications | Data Science For Beginners | Data Science Trainin...Edureka!
** Data Science Certification using R: https://www.edureka.co/data-science **
This Edureka "Data Science Applications" PPT takes you through the various domains in which data science is being deployed today, along with some potential applications of this technology. The world today runs on data and this PPT shows exactly that.
Check out our Data Science Tutorial blog series: http://bit.ly/data-science-blogs
Check out our complete Youtube playlist here: http://bit.ly/data-science-playlist
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Explains: What is Data Science? What is the difference between Data Science and Data Engineering, and between Data Science and Business Intelligence? What type of work do Data Scientists do, and what types of companies employ them? What is the job outlook for Data Science? What professional education is required?
In this presentation, I have talked about Big Data and its importance in brief. I have included the very basics of Data Science and its importance in the present day, through a case study. You can also get an idea about who a data scientist is and what all tasks he performs. A few applications of data science have been illustrated in the end.
FUTURE OF DATA SCIENCE IN INDIA
DATA SCIENCE
It is a tool that uses all kinds of data, algorithms and scientific methods. It is a very important tool as it combines two of the most important things in technology and modern science that is mathematics and computer science together. Organizing, data delivery and packaging are the three most important components involved in data science. Data Science handles data works on them and makes conclusion based on the data.
Understand the Demand of Analyst Opportunity in U.SJiaming Zhang
The slides summarize an analysis on the demand pattern of analyst opportunity (like data analyst, data science) in the U.S.
In a nutshell, it answer four questions, including the demand trend, demand source, degree and skill requirement based on the online job posting data.
This was first part of the presentation on "Road Map for Careers in Big Data" in Conjunction with Hortonworks/Aengus Rooney on 17th August 2016 in London. For those contemplating moving to Big Data from often Relational Background
Data Analytics with R, Contents and Course materials, PPT contents. Developed by K K Singh, RGUKT Nuzvid.
Contents:
Introduction to Data, Information and Data Analytics,
Types of Variables,
Types of Analytics
Life cycle of data analytics.
A Seminar Presentation on Big Data for Students.
Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. This type of data requires a different processing approach called big data, which uses massive parallelism on readily-available hardware.
In this presentation, let's have a look at What is Data Science and it's applications. We discussed most common use cases of Data Science.
I presented this at LSPE-IN meetup happened on 10th March 2018 at Walmart Global Technology Services.
Being able to make data driven decisions is a crucial skill for any company. The requirements are growing tougher - the volume of collected data keeps increasing in orders of magnitude and the insights must be smarter and faster. Come learn more about why data science is important and what challenges the data teams need to face.
Each of these roles has different requirements, but all require a solid grounding in data manipulation and analysis, as well as the ability to communicate complex ideas and insights to a variety of stakeholders. Additionally, these roles typically require proficiency with a range of data-oriented programming languages, such as Python or R, and knowledge of SQL for database management.
Running head PROFESSIONAL INTERVIEW REPORT 1PROFESSIONAL INT.docxjeanettehully
Running head: PROFESSIONAL INTERVIEW REPORT 1
PROFESSIONAL INTERVIEW REPORT 4
Experience as a Computer Scientist
Opening Statement
For this report, the professional interviewed is a computer Engineer/ Web Developer who works for Omnivision Technologies Inc., a corporation that designs and develops advance digital technologies to use in mobile phones, notebooks, security cameras etc. across the United States. The interviewee is the technical manager of the organization and works at its headquarters in Santa Clara, California and has been working in this position for the last five years. This computer science expert provided very useful information about the computer science profession and highlighted a number of challenges common in the career. Further, he provided some recommendations on how the challenges can be dealt with. From the information provided by the interviewee, it is clear that the computer science profession is full of challenges particularly regarding the fast changing technology. The interview revealed several important topics which require further research.
Methodology
The interview was conducted on a skype video call and lasted for slightly above 30 minutes. Before the interview, the interviewee was contacted one hour in advance in order to avoid an ambush. He was also made to understand that the questions which were to be asked during the interview regards the profession, its concerns and challenges. The phone call was recorded during the entire conversation and the information later transcribed and key points extracted. This report is based only on important points and not everything that the interviewee said.
Essential Background
Computer science is a field of technology that deals with studying processes that interact with data and which can be depicted as data in program form. Skills in computer science enables one to manipulate, use, or communicate digital information using programing algorithms. An expert in computer science has knowledge in computation theory as well as the practice of software systems design. Computer scientists are also popularly known as computer and information scientists and can work in a range of environments. For instance, these professionals work in private software publishers, government agencies, academic institutions, and engineering firms (Page & Smart, 2013). Wherever they work, computer scientists’ general roles include solving computing problems as well as developing new products.
The professional interviewed for this report has in-depth knowledge in computer systems and management. Through his leadership skill, he organizes the successful delivery of effective and efficient technical solutions within the company. In particular, he is responsible for planning, designing, developing, production, and testing communication systems. He is also responsible for supervising technical and operations teams, landline and cellular network, IT infrastructure, and service platforms. He ...
Full-Stack Development or Data Science, Which is the more advantageous Career...Uncodemy
Both full-stack development and data science present promising career trajectories, with the decision hinging on individual preferences, skills, and career objectives. Whether one is drawn to designing user-friendly interfaces or uncovering insights from extensive datasets, both fields play pivotal roles in shaping the technological landscape. By grasping the intricacies of each domain, individuals aspiring to join the tech industry can choose to enroll in a Data Science or Full Stack Developer Course in locations like Kurukshetra, Delhi, Hisar, Noida, Mumbai, or any other city across the nation.
Information Technology in India is an industry consisting of two major components: IT services and business process outsourcing. The information technology (IT) sector is comprised of companies that produce software, hardware or semiconductor equipment, or companies that provide internet or related services. IT Sector offers employment mostly to educated, technically qualified talented persons.
This Data Science course emphasises on Project-Based Learning to meet the learning needs of students from various background and make them job-ready. Learn Data Science like a pro and our methodology invoke thought process in the learner to solve problems. Post completion of the course, learners could independently build a Data Science solution using Machine Learning models. You would be offered a chance to secure an internship with relevant industries and participate in our hackathons.
Purpose of this presentation is to highlight how end to end machine learning looks like in real world enterprise. This is to provide insight to aspiring data scientist who have been through courses or education in ML that mostly focus on ML algorithms and not end to end pipeline.
Architecture and components mentioned in Slide 11 will be discussed in detailed in series of post on LinkedIn over the course of next few month
To get updates on this follow me on LinkedIn or search/follow hashtag #end2endDS. Post will be active in August 2019 and will be posted till September 2019
Whether you are a beginner, a transient, or a data scientist, this plan addresses each individual's needs. You can learn data science in a year if you follow this process.
Diploma in IT: Empowering Careers in the World of Technologyabieducators0
Embark on a transformative journey into the realm of Information Technology . Explore the myriad opportunities that a Diploma in IT unlocks, propelling your career into the dynamic world of technology. Whether you're a tech enthusiast or a career aspirant, this presentation unveils the pathways to success in the ever-evolving IT landscape.
Key Insights:
In-Demand Skills: Discover the highly sought-after skills that employers are looking for in the IT industry.
Career Advancement: Learn how a Diploma in IT can be your gateway to accelerated career growth and diverse job roles.
Industry-Relevant Curriculum: Explore the comprehensive curriculum designed to align with the latest industry trends and technologies.
Networking Opportunities: Unlock doors to a vast network of industry professionals, mentors, and like-minded peers.
Hands-on Experience: Understand the importance of practical, hands-on experience in shaping your IT expertise.
Join us on this informative journey to discover how a Diploma in IT can empower and shape your career in the rapidly evolving world of technology. Your future in IT starts here!
💡 visit our website for more information. 🌐 https://abi-educators.co.uk/
#DiplomaInIT #InformationTechnology #TechCareers #CareerDevelopment #ITSkills #TechEducation #CareerAdvancement #ITCurriculum #NetworkingOpportunities #TechnologyTrends #HandsOnExperience #ITJobs #ProfessionalGrowth #ITIndustry #TechEnthusiast
Following the advice in this learn guide on how to become a data analyst will put you on the right path to being a professional data scientist. No matter what sector you work in, becoming a data analyst is a rewarding path to take. Explore our in-depth learn guide on "How to Become a Data Analyst" to get started with your career if you want to learn more about how to develop a successful career in this sector and discover the numerous courses available to get needed skills and expertise. Learn all the information you require to start your career, including the skills and how to acquire them.
The Impact of Artificial Intelligence on Modern Society.pdfssuser3e63fc
Just a game Assignment 3
1. What has made Louis Vuitton's business model successful in the Japanese luxury market?
2. What are the opportunities and challenges for Louis Vuitton in Japan?
3. What are the specifics of the Japanese fashion luxury market?
4. How did Louis Vuitton enter into the Japanese market originally? What were the other entry strategies it adopted later to strengthen its presence?
5. Will Louis Vuitton have any new challenges arise due to the global financial crisis? How does it overcome the new challenges?Assignment 3
1. What has made Louis Vuitton's business model successful in the Japanese luxury market?
2. What are the opportunities and challenges for Louis Vuitton in Japan?
3. What are the specifics of the Japanese fashion luxury market?
4. How did Louis Vuitton enter into the Japanese market originally? What were the other entry strategies it adopted later to strengthen its presence?
5. Will Louis Vuitton have any new challenges arise due to the global financial crisis? How does it overcome the new challenges?Assignment 3
1. What has made Louis Vuitton's business model successful in the Japanese luxury market?
2. What are the opportunities and challenges for Louis Vuitton in Japan?
3. What are the specifics of the Japanese fashion luxury market?
4. How did Louis Vuitton enter into the Japanese market originally? What were the other entry strategies it adopted later to strengthen its presence?
5. Will Louis Vuitton have any new challenges arise due to the global financial crisis? How does it overcome the new challenges?
2. Reading is easy, comprehension is not. Hearing is easy, listening is not. Similarly, obtaining a
million bytes of data is easy, but parsing through them and forming a structured format of
information is not. Yes, a data scientist’s job is not comfortable, but staying in a comfort zone never
changes the world.
A data scientist is an artist, mathematician and engineer, all rolled in one. Formatting an
unstructured data into a structured format requires a skilled statistician
Creating algorithms to parse and output trained models/subsets of the data expects the expertise
of a machine learning engineer.
Presenting the data in a visually comprehensible and appealing manner entails the services of an
artist.
When one job profile requires these many skills, it’s not hard to see why data scientists are called
the current generation’s superheroes.
Now arises the million-dollar question, “Can I become a data scientist?”. Yes, you definitely can
because the data science field is vast and filled with opportunities that are waiting to be utilized.
In the following sections, we will analyze the data science career, the qualifications required for
the same and average remuneration that can be expected etc. Armed with this knowledge, you
can start on your exciting journey into the data science territory.
3. Data Scientist
A bachelor’s degree in a related field like Math,
Physics, Computer Science, Engineering etc. (This
is a compulsory pre-requisite to foray into the
field)
A master’s degree in a field related to data
science (This is not compulsory, but highly
preferred to rise in the ranks within the field)
Online certifications (This coupled with a solid
bachelor’s degree can provide an easy start in the
data scientist career path)
Job description
Required to mine vast amounts of unstructured data,
and then apply statistical learning, machine learning
methodologies etc. to transform into structured data.
Educational requirements
4. Part-Time: Not highly encouraged,
but increasingly opted by individuals
who love to challenge themselves
with complex data problems of
different kinds. Rather than get
boxed into a particular form of data
analysis
Full-Time: Widely opted form of
employment which ensures stability
and career growth within the chosen
industry. Helps in improving skill on a
particular focus area and becoming a
subject matter expert in said topic.
Forms of employment
IBM
Amazon
Facebook
Apple
Microsoft
Google
India: 8 Lakhs per
annum (INR)
USA: 85k per annum
(USD)
Famous recruiting
companies
Average initial salary
structure
6. Job description
A business intelligence developer is someone who makes
business data understandable to help further the
development of said concern. In colloquial terms, we could
say, a Business Intelligence (BI) developer is the layman’s
data scientist. He/ She uses various BI tools (e.g. Power BI)
to decode the obtained data sets and present it in the forms
of graphs, diagrams or reports etc. in non-technical terms,
that will be feasible for both the business owners and
customers to understand.
A bachelor’s degree (preferably in related fields like
programming or computer science)
Experience is highly valued in this field, since only
someone who has been with a given firm for a
substantial amount of time, would be able to generate
viable data for the organization’s growth.
Educational requirements
7. Forms of employment
Part-Time: Not recommended as BI developers require
extensive company knowledge in addition to technical
know-how.
Full-Time: Most preferred, since job security increases
with experience in a data science career.
Rolls Royce
Dell
Amazon
Microsoft
Discover
India: 6.5 Lakhs per annum (INR)
USA: 73.8k per annum (USD)
Famous recruiting companies
Average initial salary structure
9. A bachel or’ s degree i n fi elds li ke Stati sti cs, Engi neeri ng
etc.
Extensi ve programmi ng knowledge
Onl i ne certi fi cati ons
Job description
As descri bed i n our Machi ne Learni ng Vs Data Sci ence
bl og, a machi ne l earni ng engi neer/ sci enti st i s hi ghl y i n
demand wi thi n the data sci ence fi eld. He/ She i s the one
responsi bl e for devel opi ng the algori thm that woul d trai n
the model , whi ch i n turn wi ll analyze the gi ven data and
produce i n the form of a structured output. Thi s rol e wi l l
requi re extensi ve techni cal knowledge and a strong
background on programmi ng wi th languages l i ke R and
Python.
Educational requirements
10. Forms of employment
Part-Time: Opted by many with extensive programming skills, who
would prefer to freelance and share their expertise widely
Full-Time: Preferred by engineers who have a strong technical
background and are looking to establish their data science career.
Famous recruiting companies
Hotstar
McAfee
MakeMyTrip
Amazon
Average initial salary structure
India: 7.2 Lakhs per annum (INR)
USA: 111.5k per annum (USD)
12. Google
LinkedIn
Twitter
Facebook
Microsoft
India: 5.5 Lakhs per annum (INR)
USA: 93.5k per annum (USD)
Famous recruiting companies
Average initial salary structure
A bachelor’s degree in Math (preferably statistics)
A master’s degree (Not compulsory but usually held by most statisticians and preferable)
PhD (Will greatly help to advance in the field)Forms of employment
Part-Time: Mostly preferred as statistics is a stronghold for many fields and not just data science, due to which
many Statisticians would prefer not to limit themselves to a single industry
Full-Time: Preferred by individuals with an interest to pursue a data science career.
Job description
A statistician can be considered as the backbone for the entire data science industry since it is the statistician’s
analysis and calculation that helps all the other data science members in their exploration. A statistician should
apply mathematical theories and formula to obtain data that will help further the business
Educational requirements
14. A bachelor’s degree (preferably in Computer Science,
Bioinformatics or Engineering)
A master’s degree (Not compulsory but preferable as it will help
increase the technical knowledge greatly required to pursue this
branch of the data science career path)
Educational requirements
Job description
An Applications architect oversees the development process behind
software applications or Machine Learning (ML) Algorithms, provides the
necessary technical support for employees to understand the functioning
of the software and creates technical documents for future use.
The Applications Architect acts as the perfect bridge between a Machine
Learning Scientist/ Engineer and a Business Intelligence (BI) Developer. He/
She will have to possess both a technical know-how and a deep business
acumen, the perfectly balanced role.
15. Amazon
IBM
TVS
Wells Fargo
India: 8.1 Lakhs per annum (INR)
USA: 134.5k per annum (USD)
Famous recruiting companies
Average initial salary structure
Part-Time: Not preferred as Applications
Architects should have a clear understanding of
the business’s inner workings which may not be
available to part-time employees
Full-Time: Preferred by individuals with an
interest to excel in the data science career path.
Forms of employment
17. Job description
This is primarily an IT (Information Technology) related job which requires the Architect
to implement and maintain the complex computer systems and technical
infrastructure. An infrastructure architect will be responsible for ICT (Information and
Communication Technology) performance and security too. This is a highly popular
profile that is not only restricted to data science but compulsorily required in all
industries of the current corporate setup.
In Data Science, with the massive amounts of data that are processed, the need of an
Infrastructure Architect will always be present to help maintain the integrity and safety
of all systems and models.
Another subset of the role is the cloud infrastructure architect, who would be
responsible for all cloud computing activities.
18. A bachelor’s degree (Computer Science
or Information Technology)
A master’s degree (Not compulsory but
preferable to venture further on the data
science career path)
Part-Time: It is not preferred since
Infrastructure Architects are the first line
of defense against any safety or
performance issues. So companies
would prefer to have them full-time to
ensure the smooth functioning of all
systems.
Full-Time: Preferred by companies and
individuals in the field.
Educational requirements
Forms of employment
Ford
IBM
Accenture
Infosys
India: 9 Lakhs per annum
(INR)
USA: 126.4k per annum
(USD)
Famous recruiting companies
Average initial salary
structure
19. Hence, as seen above the scope of data
science careers is quite high and with some
careful research and the proper
qualifications, you could easily start on the
path of your data science career.
For those who have completed their UG or
PG courses and are looking for a foray into
the field, the Henry Harvin Data Science
Courses would be a wonderful online
platform to obtain your certifications and
the coveted data scientist education.
Hurry up to climb up the ladder of
opportunity!
