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Best Resources To Learn Data Science In Hindi
Data science tutorials and courses are usually comprehensive, which includes fundamentals of data science, statistics, mathematics, hypothesis, programming, analysis etc. And thus can be exhaustive for many young minds who are recently kick-starting their career in data science. Such in-depth intensive subjects can be even more gruelling to understand if not learnt in a language learners are comfortable with.
In India, according to data, 43.63% of people speak Hindi, and out of which, 25% regards Hindi as their native language. Thus, many a time, young professionals struggle to grasp complex data science topics due to the lack of understanding the language.
So, if you are willing to transform your career with in-demand data science skills, here are the best paid as well as free resources where one can learn data science in Hindi.
Also Read: Top 7 Resources To Learn MLStudio
Hands-on Machine Learning Course
Source: Udemy
About: This is an all-in-one, machine learning course provided by Udemy involving deep learning, natural language processing and Python knowledge in Hindi. This course of 16.5 hours on-demand video has been designed to include the maximum concept of machine learning without any prerequisite of machine learning knowledge. Not only this course will teach how to analyse the data and feed it to ML models, but also hands-on making predictions using logistic regression, k-nearest neighbours and Naive Bayes. With this course, learners can get a solid understanding of machine learning before actually entering into the field.
Check out the course here.
edureka! Hindi
Source: edureka
About: edureka! Hindi is a youtube channel by edureka, which provides high-quality videos, webinars, sample classes and lectures in Hindi. Encompassing subjects like Python, Scikit-Learn, machine learning, SQL Injection, to name a few, these video tutorials can help gaining fundamental data science knowledge for beginners to be industry-ready. In their 35 minutes tutorial video on data science, not only they have covered detailed and comprehensive understanding of data science but also explained various aspects of data and its lifecycle described quickly in Hindi. Started in 2018, the channel — eureka! Hindi has over 100K followers on YouTube.
Watch the videos here.
Analytics India Guru
Source: Analytics India Magazine
About: Analytics India Guru is a set of video tutorials by Analytics India Magazine on YouTube that shares data science knowledge in Hindi. Starting from “what is a neural network” to “applications of GANs,” these tutorials provide short five-minute explanatory videos of various aspects of data science. With these tutorials, one can quickly get their hands on many complex topics of the field and understand in-depth information on the subject.
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How To Build A Data Science Career In 2021
For this week’s data science career interview, we got in touch with Dr Suman Sanyal, Associate Professor of Computer Science and Engineering at NIIT University. In this interview, Dr Sanyal shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.
With industry-linkage, technology and research-driven seamless education, NIIT University has been recognised for addressing the growing demand for data science experts worldwide with its industry-ready courses. The university has recently introduced B.Tech in Data Science course, which aims to deploy data sets models to solve real-world problems. The programme provides industry-academic synergy for the students to establish careers in data science, artificial intelligence and machine learning.
“Students with skills that are aligned to new-age technology will be of huge value. The industry today wants young, ambitious students who have the know-how on how to get things done,” Sanyal said.
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Procedure To Become An Air Hostess/Cabin Crew
Minimum educational required – 10+2 passed in any stream from a recognized board.
The age limit is 18 to 25 years. It may differ from one airline to another!
Physical and Medical standards –
- Females must be 157 cm in height and males must be 170 cm in height (for males). This parameter may vary from one airline toward the next.
- The candidate's body weight should be proportional to his or her height.
- Candidates with blemish-free skin will have an advantage.
- Physical fitness is required of the candidate.
- Eyesight requirements: a minimum of 6/9 vision is required. Many airlines allow applicants to fix their vision to 20/20!
- There should be no history of mental disease in the candidate's past.
- The candidate should not have a significant cardiovascular condition.
You can become an air hostess if you meet certain criteria, such as a minimum educational level, an age limit, language ability, and physical characteristics.
As can be seen from the preceding information, a 10+2 pass is the minimal educational need for becoming an air hostess in India. So, if you have a 10+2 certificate from a recognized board, you are qualified to apply for an interview for air hostess positions!
You can still apply for this job if you have a higher qualification (such as a Bachelor's or Master's Degree).
So That I may recommend, joining Special Personality development courses, a learning gallery that offers aviation industry courses by AEROFLY INTERNATIONAL AVIATION ACADEMY in CHANDIGARH. They provide extra sessions included in the course and conduct the entire course in 6 months covering all topics at an affordable pricing structure. They pay particular attention to each and every aspirant and prepare them according to airline criteria. So be a part of it and give your aspirations So be a part of it and give your aspirations wings.
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For more information:
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Phone : wa.me//+919988887551
Address: Aerofly International Aviation Academy, SCO 68, 4th Floor, Sector 17-D, Chandigarh, Pin 160017
Email: info@aerofly.co.in
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Your Data Architecture: Simple Best Practices for Your Data Strategy
If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.
If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.
In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.
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Level Up 7 Data Science Skills Through YouTube
We are all familiar with the modern game design, that champions or heroes are always equipped with certain attributes and specialties. For example, Dota heroes are scored based on the aspects of agility, intelligence, and strength. To excel on the battlefield, the hero needs to have above-average scores among all attributes while additionally specialized in at least one.
So what if we think of learning data science as playing a game where all of us possess multi-dimensional abilities. Playing video games demands constantly sharpening our skills with weapons, training, or magic potion. This resembles us learning through reading, tutorials, and of course those YouTube learning resources mentioned later in this article.
First of all, let’s walk through seven essential skills that guarantee your wins in the data science game.
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5 Data Science Podcasts To Follow in 2021
If we only learn data science through a rigid curriculum created by universities or online courses from Coursera or Udemy, we may find the learning process too boring. If you ever find yourself losing motivation in this long journey of studying data science, you may just need some podcasts to break the routine and get some inspiration. The major difference between these two approaches of learning is that the former focuses on theory and concepts, whereas the latter introduces more practical experience and projects that add flesh to the bones.
Listening to podcasts is a great way to absorb knowledge while you are commuting or doing the chores. One of the amazing apps that I recommend using is called “Airr” which allows users to highlight the content of the podcast and transcribe the highlight into notes. This tool is especially useful for technical podcasts since information is more easily erased if you are more of a visual learner than an auditory learner. Therefore, putting it into notes somewhere would assist in transforming them into long term memory.
On the other hand, if you are more of a visual person who prefers to learn through reading, then have a read of the Data Science website list that I curated :)
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