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kenresearchcompany · 2 years

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India Executive Education Market: Outlook, Revenue, Growth Rate, Trends, Share, Size, Opportunities and Forecast to 2027

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Increasing Technology adoption and convenience offered by the education providers will propel students to adopt Executive Education practices: Ken Research

Ambitious government initiatives, increasing adoption of automation in India, paired with economic feasibility of opting for executive education courses for working professionals has led to the growth of Executive Education market in India.

Thriving technology adoption and convenience offered by the education providers are primary reasons for students to adopt Executive Education practices.

30-34 Years age group is the prime segment of Executive Education students, with ~40% of market share of the total Enrolments.

Rising Adoption of Digitalization: While the COVID-19 epidemic shook the world, remote work began to supplement industrial demands in India due to market-leading technological tools. As a result, the strategy to talent acquisition and deployment has shifted. Virtual hiring, training, and conferencing were the foundation upon which the formal economy thrived. The Indian workforce has been steadily shifting to meet the rising needs of contemporary working through digitalization. The epidemic highlighted the growing reliance on technology in all sectors. Organizations tapped on the remote work culture and automated business procedures that have long formed the foundation of many successful enterprises. Big data analytics, digital marketing, cybersecurity, AI, and machine learning are among the most popular courses, with product management following closely after.

Optimistic Growth of Customized MDP Segment: All the major education institutes are predicted to have an optimistic growth on customized programs along with tie-ups of corporations and government agencies. The MDP segment is poised to grow the most with ~2.8% CAGR from FY’22 to FY’27.

Government Initiatives toward Education Sector: The National Accreditation Regulatory Authority Bill for Higher Education, the Foreign Educational Institutions Bill, and 100% FDI in India's educational sector are only a few of the measures taken by the Indian government to liberalize the sector. The Indian government has taken a variety of actions, such as adding new IITs and IIMs and providing research academics at most government universities with educational funding.

Rise of Niche vertical focused e-Learning Players: Executive Education sector is expected to grow at ~3.3% CAGR from FY’22 to FY’27, where a high demand and quick adoption of online and virtual learning programs is expected. Furthermore, virtual learning platforms have seen a rise in terms of Revenue as well. The NITI Aayog and Indian Education sector promote the Indian EdTech firms, which have garnered private equity investments totaling more than $4 billion over the past five years.

Integrating Education with Skill Requirements: In cooperation with learning and EdTech firms, some B-schools and universities have started to provide executive learning programs for professional development and career promotion, providing catalogues of online courses, courses, and certifications. Businesses have been making investments in digital learning strategies and content in recent years, working with learning and EdTech firms to develop online course, program, and certification catalogues.

The report titled “India Executive Education Market Outlook to FY’2027: Cascading growth driven by rising skill gap, tailored executive education courses, coupled with rising adoption of digitalization by Corporates” by Ken Research suggests that the India Executive Education market is expected to grow further in the near future, with increasing adoption of technology and awareness among working executives of India. The market is expected to register a positive CAGR of ~3% in terms of Revenue, during the forecast period of FY’22-FY’27.

Key Segments Covered in India Executive Education Market

By Type of Programs

Executive MBA

MDP

India Executive Education Market – EMBA Segmentation

By Mode of Funding

Company-Sponsored

Self-Funded

By Duration of Courses

0-12 Months

12-24 Months

>24 Months

By Type of Courses

Part-Time

Full-Time

Others

By Number of Electives Offered

0-10

10-20

By Type of Institution

Government

Private Institutions

By Mode of Learning

Virtual, In-Person

Hybrid

India Executive Education Market – MDPs Segmentation

By Course Duration

<1Week

1 Week – 1Month

>1Month

By Type of Courses

Strategy

Leadership

Management

Marketing & Sales

Finance & Accounting

Others

By Type of Institution

Government

Private Institutions

By Mode of Learning

Virtual

In-Person

Hybrid

Key Target Audience

Government Executive Education Providers

Private Executive Education Providers

Virtual Learning Providers

Corporations and Institutions offering Employee Training

Research organizations and consulting companies

Government bodies such as regulating authorities and policy makers

Organizations, forums and alliances related to Executive Education

Request for Sample Report @ Request for Sample Report @ https://www.kenresearch.com/sample-report.php?Frmdetails=NTc0NDMx

Time Period Captured in the Report:

Historical Period: FY’17-FY’22P

Forecast Period: FY’22P-FY’27F

Major Executive Education Providing Institutions in India:

E-MBA Course Providers

MDP Course Providers

Virtual Players

IIM Ahmedabad

IIM Bangalore

ISB Hyderabad

Great Lakes Institute of Management

ICFAI Business School

XLRI

IIM Calcutta

All India Management Association

P.Jain Global Institute

IIFT Delhi

Others

IIM Ahmedabad

IIM Bangalore

IIM Calcutta

IIM Lucknow

ISB Hyderabad

Great Lakes Institute of Management

XLRI

All India Management Association

MDI Gurgaon

IIM Kozhikode

Others

Jaro Education

Emeritus

Jigsaw Academy

Hughes Education

NIIT Imperative Ltd.

Coursera

Times Professional Learning

UpGrad

Key Topics Covered in the Report

India Socio-Demographic Overview and Education Market Snapshot

India Executive Education Market Overview

Executive Education Market Ecosystem in India

India Executive Education Market Size and Segmentation

E-MBA Services Industry Overview

E-MBA Services Industry Market Segmentation

E-MBA Services Industry Demand Analysis

E-MBA Services Industry Competitive Landscape

E-MBA Services Industry Future Market Segmentation

MDP Services Industry Overview

MDP Services Industry Market Segmentation

MDP Services Industry Demand Analysis

MDP Services Industry Competitive Landscape

MDP Services Industry Future Market Segmentation

Trends and Developments in India Executive Education Market

Trends and Developments in End User Preferences

SWOT Analysis of India Executive Education Market

Porter 5 Forces Analysis of India Executive Education Market

Growth Drivers in India Executive Education Market

Issues and Challenges in India Executive Education Market

Supervisory Framework for Executive Education Market in India

Impact of COVID-19 on Demand and End user preferences in Executive Education Market

Cross Comparison of Major E-MBA and MDP Providers across major decision-making parameters (such as type of programs, student enrolments, fees of the program, value propositions and others)

Market Share (By Revenue), Enrolment Number and Total Number of Programs, of Major Executive Education Providers in India, FY’22P

Snapshot of e-Learning Providers in Executive Education in India

Comparative Assessment: Company Overview (Inception Year, Office Location, Number of Programs, USP, Number of Alumni, Academic Partners, Average Fees, Duration of Courses, Mode of Delivery, Eligibility Criteria, Key Target Audience, Value Proposition, Key Offerings and Others)

Future of Executive Education Space in India

Outlook and Projections of Market Size of Executive Education Market in India, by Revenue (INR Cr) and Number of Programs, FY’22-FY’26

Industry Best Practices

Opportunities in the demand side

Industry Speaks

For more information on the research report, refer to below link:-

India Executive Education Market Outlook to FY’2027: Ken Research

Related Reports

UK Executive Education Market Outlook to 2023 - By Type of Management Development Programs (Finance, Strategy, Leadership, Ethics and others), By Duration of the Course (1 day, 1-2 days, 2-3 days, 3-5 days, 5-10 days and 10+ days) and By Type of Universities (Private and Public)

Singapore Executive Education Market Outlook to 2023 - By Type of Program (EMBA and MDP), By Funding of the Program MDPs (Company Sponsored and Self Funded) and EMBA (Self Funded, Partial Funding and Company Sponsored), By Duration MDP (1-7 days, 7-14 days and more than 14 days) and EMBA (up to 12 Months, 12-24 Months and More than 24 Months)

Australia Executive Education Market Outlook to 2024 –Driven by Rising Popularity of Online Education and Launch of Innovative Programs

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Ken Research Ankur Gupta, Head Marketing & Communications [email protected] +91-9015378249

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mutabikim · 3 years

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mutabıkım

Mutabıkım, an e-Reconciliation Solution, is a solution developed by MDP Group within the scope of e-transformation. It enables companies to manage all reconciliation processes in the most effective and fastest way by transferring them to the digital environment.

MDP Group offers innovative, creative and high added value solutions to meet the needs of companies in line with its experience in consultancy, software development and Fintech since 2013.

MDP Group, which has realized more than 1000 projects by working with more than 300 customers, accompanies companies' digital transformation journeys by providing SAP, e-Transformation and Web/Mobile application development services. In addition, MDP Group also achieves new achievements in the field of digital innovation with its R&D activities, data analytics and machine learning software developments.

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hiba1810-blog · 6 years

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Marketing Certification courses

Marketing certification courses Management Development Programmes (MDP) is a marketing certification courses which provide participants fundamentals like Managerial Effectiveness, Team Building, Cost Management, Sales & Marketing skills, Management of Organizational Change, etc to emerging issues like Big Data, Creativity & Innovation, and Leadership. It also provides an opportunity to refocus, to immerse themselves in the latest thinking about best practice for business analytics courses in management, and provide them with personal and professional tools to strengthen their effectiveness as a manager and leader. The programme also provides a global context for enhancing supply chain management, from the challenges of leading change and transformation, to working more effectively in uncertain environments and harnessing technology to ensure that systems and procedures are optimised. Coaching and Mentoring as developmental tools are known to impact individual and organisational performance to the tune of 4x, as compared to training. Developing coaching and mentoring competency is, therefore, gaining importance in today's competitive world. Organisations are increasingly realising the need to bolster continuous learning efforts as they strive towards preparing future leaders. The pedagogy employed involves a variety of teaching methods: case studies, simulations, role plays, closed group analyses and applied to learn projects, interspersed with lecture sessions on theory and practice. The sessions are essentially interactive, and participants are encouraged to question assumptions, identify opportunities, solve complex problems, develop operational performance, boost productivity, and in the process, build the sustainable competitive advantage. The knowledge and insights gained as a result of such sessions have immediate applications for high-priority management challenges. As a result, participants, as well as the sponsoring organization, receive a rapid –and lasting– return on investment. Programme Objective is to facilitate the Appreciation of the various roles of the coach and mentor, Development of skills and competencies needed for managers to serve as effective mentors and coaches, Appropriate usage of coaching and mentoring techniques, styles and methods for enhancing productivity and performance and Enhancing team members' performance through continuous and effective feedback. Programme Benefits Participants would avail the following opportunities: • Design and facilitate a successful coaching and mentoring programme in their organisation. • Appreciate the roles and responsibilities of key players in a coaching/mentoring system. • Foster and facilitate an effective culture of coaching and mentoring relationships in an organisation. • Develop a personal development plan as an action plan for the self and protégés' growth and development. For more details please visit the site http://www.spjimr.org/mdp

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certaintragedyluminary · 3 years

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Data Scientist course

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arohi19 · 3 years

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Top 5 Data Science Courses To Study In India

Passionate about gadgets and technology, he has created several projects using Arduino. Well versed with networking and various programming languages, Suvendu is developing new hacking tools using Python. He has worked as an Assistant Professor at Sikkim Manipal University & Guest Faculty at National Institute of Pharmaceutical Education and Research. He has presented several research papers in international conferences.

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isbmainstitute · 2 years

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In today's time, technology is increasing rapidly. Every organization uses a data analytics process to make better decisions. ISBMA institute offers MDP on data analytics for students. In data analytics, all the information gets captured in the systems software. Here we teach our students how to collect customer data for business purposes. The data scientist helps the organization make an informed decision for business growth.

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nshah654322 · 3 years

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Management Development Programs (MDP's) by ISBM Institute.

Indian School Business Management & Administration (ISBM) offers management development programs to professionals worldwide. The institute's mission is to improve the performance of any working professionals through training, coaching and consulting services. The MDPs are designed for administrators who have been in their position less than three years or those with no experience as an administrator. These programs are highly customizable to meet the individual needs of schools and districts around the US

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salmanistm12345 · 1 year

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MDP On Data Analytics

Every industry uses data analytics to get customer information in today's technology world. An individual who wants to pursue MDP in data analytics applies from ISTM Institute. With this data analytics course, students will learn techniques for examining the data. There are specialized systems and software available. For more information about ISTM, visit https://www.istm.org.in/

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educationinstitutions · 3 years

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Status Institute Of Management

Those who're interested in teaching can pursue a career in academics after finishing Master Degrees in Law. The College of Engineering’s sturdy alliance with industries ensures relevancy in school rooms and analysis labs. Programs corresponding to ‘MUJCAL’ – a enterprise-schooling partnership, provides excessive-attaining college students skilled experience.

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sciforce · 4 years

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Reinforcement Learning and Asynchronous Actor-Critic Agent (A3C) Algorithm, Explained

While supervised and unsupervised machine learning is a much more widespread practice among enterprises today, reinforcement learning (RL), as a goal-oriented ML technique, finds its application in mundane real-world activities. Gameplay, robotics, dialogue systems, autonomous vehicles, personalization, industrial automation, predictive maintenance, and medicine are among RL's target areas. In this blog post, we provide a concrete explanation of RL, its applications, and Asynchronous Actor-Critic Agent (A3C), one of the state-of-the art algorithms developed by Google's DeepMind.

Key Terms and Concepts

Reinforcement learning refers to the type of machine learning technique enabling an agent to learn to interact with an environment (area outside the agent's borders) by trial and error using reward (feedback from its actions and experiences). The agent seeks ways to maximize the reward via interacting with the environment instead of analyzing the data provided. The agent is a learning controller taking actions in the environment and receives feedback in the form of reward.

The environment, space where the agent gets everything needed from a given state. The environment can be static or dynamic, and its changes can be stochastic and deterministic correspondingly. It is usually formulated as Markov decision process (MDP), a mathematical framework for decision-making development.

However, real-world situations often do not convey information to commit a decision (some context is left behind the currently observed scene). Hence, the Partially Observable Markov Decision Processes (POMDPs) framework comes on the scene. In POMDP the agent needs to take into account probability distribution over states. In cases where it’s impossible to know that distribution, RL researchers use a sequence of multiple observations and actions to represent a current state (i.e., stack of image frames from a game) to better understand a situation. It makes possible to use RL methods as if we are dealing with MDP.

The reward is a scalar value that agents receive from the environment, and it depends on the environment’s current state (St ), the action the agent has performed grounding on the current state (At ), and the following state of the environment (St+1):

Policy (π) stands for an agent’s strategy of behavior at a given time. It is a mapping from the state to the actions to be taken to reach the next state. Speaking formally, it is a probability distribution over actions in a given state, meaning the likelihood of every action in a particular state. In short, policy holds an answer to the “How to act?” question for an agent.

State-value function and action-value function are the ways to assess the policy, as RL aims to learn the best policy. Value function V holds an answer to the question “How good current state is?”, namely an expected return starting from the state (S) and following policy (π).

Sebastian Dittert defines the action-value of a state as “the expected return if the agent chooses action A according to a policy π.” Correspondingly, it is the answer to “How good current action is?”

Thus, the goal of an agent is to find the policy () maximizing the expected return (E[R]). Through the multiple iterations, the agent’s strategy becomes more successful.

One of the most crucial trade-offs for RL is balancing between exploration and exploitation. In short, exploration in RL aims at collecting experience from new, previously unseen regions. It potentially holds cons like a risk, nothing new to learn, and no guarantee to get any useful further information. On the contrary, exploitation updates model parameters according to gathered experience. In its turn, it does not provide any new data and could not be efficient in case of scarce rewards. An ideal approach is making an agent explore the environment until being able to commit an optimal decision.

Reinforcement Learning vs. Supervised and Unsupervised Learning

Comparing RL with AI planning, the latter does cover all aspects, but not the exploration. It leads to computing the right sequence of decisions based on the model indicating the impact on the environment.

Supervised machine learning involves only optimization and generalization via learning from the previous experience, guided with the correct labels. The agent is learning from its experience based on the given dataset. This ML technique is more task-oriented and applicable for recognition, predictive analytics, and dialogue systems. It is an excellent option to solve the problems having the reference points or ground truth.

Similarly, unsupervised machine learning also involves only optimization and generalization but having no labels referring to the environment. It is data-oriented and applicable for anomaly and pattern discovery, clustering, autoencoders, association, and hyper-personalization pattern of AI.

Asynchronous Advantage Actor-Critic (A3C) Algorithm

The A3C algorithm is one of RL's state-of-the-art algorithms, which beats DQN in few domains (for example, Atari domain, look at the fifth page of a classic paper by Google Deep Mind). Also, A3C can be beneficial in experiments that involve some global network optimization with different environments in parallel for generalization purposes. Here is the magic behind it:

Asynchronous stands for the principal difference of this algorithm from DQN, where a single neural network interacts with a single environment. On the contrary, in this case, we've got a global network with multiple agents having their own set of parameters. It creates every agent's situation interacting with its environment and harvesting the different and unique learning experience for overall training. That also deals partially with RL sample correlation, a big problem for neural networks, which are optimized under the assumption that input samples are independent of each other (not possible in games).

Actor-Critic stands for two neural networks — Actor and Critic. The goal of the first one is in optimizing the policy (“How to act?”), and the latter aims at optimizing the value (“How good action is?”). Thus, it creates a complementary situation for an agent to gain the best experience of fast learning.

Advantage: imagine that advantage is the value that brings us an answer to the question: “How much better the reward for an agent is than it could be expected?” It is the other factor of making the overall situation better for an agent. In this way, the agent learns which actions were rewarding or penalizing for it. Formally it looks like this:

Q(s, a) stands for the expected future reward of taking action at a particular state

V(s) stands for the value of being in a specific state

Challenges and Opportunities

Reinforcement learning’s first application areas are gameplay and robotics, which is not surprising as it needs a lot of simulated data. Meanwhile, today RL applies for mundane tasks like planning, navigation, optimization, and scenario simulation in various verticals chains. For instance, Amazon used it for their logistics and warehouse operations’ optimization and for developing autonomous drone delivery.

Simultaneously, RL still poses challenging questions for industries to answer later. Given its exploratory nature, it is not applicable in some areas yet. Here are some reasons:

Meanwhile, RL seems to be worth time and resources investment as industry players like Amazon show. Just give it some time, since investment in knowledge always requires it.

#reinforcement learning #machine learning #supervised learning #unsupervised learning #artificial intelligence #data science #ai

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kajalkumari1 · 4 years

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Python Career Opportunities – Which one will you choose?

The Next Big Thing to look up onto is Python and there is no doubt about that. Questions related to its worth, career opportunities, or available jobs are not to be worried about. As Python is rapidly ceasing the popularity amongst developers and various other fields, its contribution to the advancement of your career is immense.

There are reasons why Python is “the one”. It is easily scripted language that can be learned quickly. Hence reducing the overall development time of the project code. It has a set of different libraries and APIs that support data analysis, data visualization, and data manipulation.

Python Career Opportunities

Number of Python Jobs

While there’s a high demand for Python developers in India, the supply is really, really low. To testify this, we’ll take account of an HR professional statement. The professional was expected to recruit 10 programmers each for both Java and Python. About a hundred good resumes flooded in for Java, but they received only 8 good ones for Python. So, while they had to go through a long process to filter out good candidates, with Python, they had no choice but to take those 8 candidates.

What does this tell you about the situation? Even though Python has easy syntax, we really need more people in India to upskill themselves. This is what makes it a great opportunity for Indians to get skilled in python. When we talk about the number of jobs, there may not be too many for Python in India. But we have an excellent number of jobs per Python programmer.

Job boards like Indeed and Naukri offer around 20,000 to 50,000 job listings for Python and this shows that Python career opportunities in India are High. Choosing Online Python Classes in Lucknow to pursue your career is a good choice. The below stats shows the total job postings of the major programming languages.

Types of Python Jobs

So what types of jobs can you land with Python?

Well, for one, Python scope is intensive in data science and analysis. Clients often want hidden patterns extracted from their data pools. It is also preferred in machine learning and artificial intelligence. Data scientists love Python. Also, in our article on applications of Python, we read about how Python is used everywhere in web development, desktop applications, data science, and network programming.

Python Job Profiles

With Python on your resume, you may end up with one of the following positions in a reputed company:

1. Software Engineer

· Analyze user requirements

· Write and test code

· Write operational documentation

· Consult clients and work closely with other staff

· Develop existing programs

2. Senior Software Engineer

· Develop high-quality software architecture

· Automate tasks via scripting and other tools

· Review and debug code

· Perform validation and verification testing

· Implement version control and design patterns

3. DevOps Engineer

· Deploy updates and fixes

· Analyze and resolve technical issues

· Design procedures for maintenance and troubleshooting

· Develop scripts to automate visualization

· Deliver Level 2 technical support

4. Data Scientist

· Identify data sources and automate the collection

· Preprocess data & analyze it to discover trends

· Design predictive models and ML algorithms

· Perform data visualization

· Propose solutions to business challenges

5. Senior Data Scientist

· Supervise junior data analysts

· Build analytical tools to generate insight, discover patterns, and predict behavior

· Implement ML and statistics-based algorithms

· Propose ideas for leveraging possessed data

· Communicate findings to business partners

Python Future

While many top companies are stuck with Java, Python is one of the old yet trending technologies. The future of Python is bright with :

1. Artificial Intelligence

Artificial Intelligence is the intelligence displayed by machines. This is in contrast to the natural intelligence displayed by humans and other animals. It is one of the new technologies taking over the world. When it’s about AI, Python is one of the first choices; in fact, it is one of the most-suited languages for it.

For this purpose, we have different frameworks, libraries, and tools dedicated to letting AI replace human efforts. Not only does it help with that, but it also raises efficiency and accuracy. AI gives us speech recognition systems, autonomous cars, etc.

The following tools and libraries ship for these branches of AI:

· Machine Learning – PyML, PyBrain, scikit-learn, MDP Toolkit, GraphLab Create, MIPy

· General AI – pyDatalog, AIMA, EasyAI, SimpleAI

· Neural Networks – PyAnn, pyrenn, ffnet, neuro lab

· Natural Language and Text Processing – Quepy, NLTK, genism

2. Big Data

Big Data is the term for data sets so voluminous and complex that traditional data-processing application software is inadequate in dealing with them.

Python has helped Big Data grow, its libraries allow us to analyze and work with a large amount of data across clusters:

· Pandas

· scikit-learn

· NumPy

· SciPy

· GraphLab Create

· IPython

· Bokeh

· Agate

· PySpark

· Dask

3. Networking

Python also lets us configure routers and switches, and perform other network-automation tasks cost-effectively. For this, we have the following Python libraries:

· Ansible

· Netmiko

· NAPALM(Network Automation and Programmability Abstraction Layer with Multivendor Support)

· Pyeapi

· Junos PyEZ

· PySNMP

· Paramiko SSH

All these technologies rely on Python today and tomorrow.

Top Organizations Using Python

With its extreme popularity and powerfulness, Python is preferred by unicorns too:

1. NASA & ISRO

NASA and ISRO use Workflow Automation System (WAS), an application written and developed in Python. It was developed by NASA’s shuttle-support contractor USA (United Space Alliance).

NASA also uses Python for APOD (Astronomy Picture Of the Day), API, PyTransit, PyMDP Toolbox, EVEREST.

2. Google

Who, on this Earth, lives and doesn’t know Google? We use it for everything – sometimes, even to find answers to life’s deepest questions. Google uses Python for its internal systems, and its APIs for report-generation, log analysis, A/Q and testing, and writing core search-algorithms.

3. Nokia

This one reminds me of Nokia 3310, the pocket phone that could break a tile. Nokia makes use of PyS60 (Python for S60). It also uses PyMaemo (Python for Maemo) for its S60 (Symbian), and Maemo (Linux) software platforms.

4. IBM

An American multinational technology company headquartered in New York, IBM uses Python for its factory tool control applications.

5. Yahoo! Maps

Maps is an online mapping portal by Yahoo! It uses Python in many of its mapping lookup services and addresses.

6. Walt Disney Feature Animation

WDFA uses Python as a scripting language for animation. All the magic that happens in Disneyland has a bit of Python behind it.

Why Python?

So, after all this Python career opportunities talk, why should you take Online Python Classes in Lucknow? What has it to offer to you? What’s the scope of Python? Let’s see.

· Its simplicity and conciseness make it perfect for beginners.

· It has a large community that continuously contributes to its development.

· Because of the highly demand-supply ratio, it provides excellent career opportunities, especially in India.

· We have a number of frameworks to make web development easy as pie.

· Python is the preferred language for Artificial Intelligence and Machine Learning.

· Raspberry Pi, a microcomputer, lets us make our own DIYs with Python, at prices that do not blast holes in your pockets.

· Both startups and corporates, make extensive use of Python, thanks to its powerfulness and simplicity.

· Python has been consecutively topping the most loved programming language on the StackOverflow developers survey report.

· StackOverflow survey reports showed us that Python is the fastest growing language in high-income countries. IBM used the STL model to predict the future growth of major languages in 2020 and it seems Python is going to leave everyone behind.

Why is Python in demand?

According to expert research, there is a huge gap between demand and supply of python developers/experts across countries like India, the USA, and more. As a result, the available python developers are paid thrice of that of actual salaries to fill the scarcity. This is an important lesson for all those who are doubting the career opportunities with python and also lacking a good hold in python. Expertise in python by gaining experience or even through online python certification training. It adds value to your resume and all-in-all to your overall career goal.

Python Skills

After knowing all the opportunities that Python holds, its good to know all the ins and out to it. Focus is always on skill first so that you stand out amongst others. They can be broken down as follows:

· Core Python (Basic knowledge between Python 2 and Python 3 is sufficient, complete knowledge of all modules is not required)

· Web Frameworks (Learn common Python frameworks such as Django or Pandas)

· Object-relational mappers (Ability to connect to the database with the help of ORM rather than SQL )

· Understand Multiprocess Architecture (Ability to write and manage threads for high-performance)

· RESTful APIs (understand how to use them and able to integrate components with them)

· Building Python Applications (One should know how to package up a code and deployment and release)

· Good communication and designing skills (Able to communicate well with members as well as implement servers that are scalable, secure and highly available)

This was all in the Python career opportunities article that provides you benefits by taking Online Python Classes in Lucknow.

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