How to become a successful Data Scientist

Introduction:

Data Science is the most emerging area for modern application development and acts as an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured.

As per the modern technology trends, it might seem strange to be making predictions about 2022, still when we are about to have far from certain how the remainder of 2021 is going to play out. Here at the present scenario, it is very difficult to predict how the world-changing events of this year, but one thing is clear: that technology has been affected just as much as every other part of our lives. For example, many applications that we are going to use like social media applications now a day are completely intelligent and smart enough.  They are using the AI technique to create more powerful applications which is very much effective and trendy in now a day.

Why Data Science is important for Modern Technology? 

1. They are used to provide more accurate data for the processing which yields accurate results.
2. They are used to support highly efficient algorithms, so it is having high demand and explores many areas of technology.
3. Analytics is everywhere, So, during the design of the application, it imparts the analytics more deeply and clearly.
4. It is only becoming more important as it has a range of related skills.

Here In this blog, I am going to discuss some most trendy ideas of Data science which really let you help to understand the importance of Data Science and provides you with the way to become a good Data Scientist. 

Prerequisites for Being a Data Scientist:

1. Bases of Artificial Intelligence is a must as without this one can’t understand the concept of Data Science.
2. One should have a good knowledge of Python languages and their packages (includes Python, Numpy, Matplotlib, Pandas, Scikit-learn, Keras, and TensorFlow).
3. You must need to have the fundamental skill of Essential Statistics & Essential Mathematics 
4. You need to understand the concept of Data Pre-processing. 
5. Understanding the concept of Machine Learning that includes Supervised, Unsupervised, Semi supervisor and Reinforcement learning Algorithms is very essential for one to be a good Data Scientist.
6. The concept of Deep Learning, Computer vision, Natural Language Processing, R Programming, and Power BI is also essential. If You have the idea of these then it will add extra mileage to your career. 

Identification of Problems:

1. As Artificial Intelligence is considered as a mother origin of intelligence so, it is more demandable technology, and it makes Data Science more effective.
2. If you need to understand the concept, then “Deep fake” searches are one of the most important topics.
3. This concept is most widely and effectively used by social media for making something more viral for publicity. Examples are Instagram, Facebook, WhatsApp, etc. 
4. The Deep fake is now becoming the interest when public figures are deep faked, and the media gets hold of it.
5. This concept enables the concept of artificial intelligence in a more real sense, and it provides the way to manipulate or create content to represent someone else.
7. In the Deep Fake technique, we are mostly taking an image or video or audio clip of one person that can be get modified to someone else’s likeness

Choosing the best programming language to develop applications:

1. If I need to say the presentation of facts, then the role of Programming language is very important. 
2. Among all the available sets of programming languages, Python is very a popular programming language created by Guido van Rossum which was get released in the year 1991. It is the Diverse Languages Poised to Embrace AI
3. Python is a more powerful language that offers great tools for data crunching and preparation, as well as for complex scientific data analysis and modeling. 
4. Python today has multiple implementations including Jython, scripted in Java language for Java Virtual Machine so it supports most of the similar features like JAVA support.
5. IronPython is the new variety that is written in C# for the Common Language Infrastructure, and PyPy version is written in RPython and translated into C. 
6. Most of the Python modules work on a community development model and are open-source and free.

End-to-end AI based solutions:

1. In the present situation, the demand for AI is getting increasing day by day. 
2. The most important concern is Business Intelligence and Predictive Analytics because It uses the data for insight and Human in the loop actions.
3. As you know the Data Science uses the AI concept in a more deep sense so it can act as a third-party interface designing also.
4. A Third-party module is defined as any code that has been written by a third party (neither you nor the python writers (PSF)). Examples include things like requests that simplify HTTP requests and nose that help with unit/integration testing.
5. When we need to write any program then we must need to write on our own, without any modules or outside help. 
6. As a good data scientist, You should have a better experience of the modules such as Tkinter and CSV. 
7. These modules are part of a library of standard modules that came packaged with your install which the developers have deemed useful or necessary for your daily python usage.

Data analysts as a prospect:

In the present scenario, analytics is everywhere. One cannot ignore the role of analytics in Data Science. As per the current review and expert suggestions we can say that the Market for Data analytics is growing across the world rapidly and it is trendier nowadays. 

The Data Analyst is used to provide a strong growth pattern for the developers, and it is used to translates into a great opportunity for all the IT Professionals. In order to define the domain Professional groups in a better sense, who are used to continue enjoying the benefits are:

• Developers and Architects
• BI /ETL/DW professionals
• Senior IT Professionals
• Testing professionals
• Mainframe professionals
• Freshers

Kaggle a tool for Data Analytics:

Kaggle is a more popular tool that is being used more widely nowadays by most professionals and it has grown quickly to become the world's largest data science community. 

As per the review analysis on Kaggle many budding data scientists now start with Kaggle to begin their machine learning journey.  And post the progress of their machine learning projects in real-time.

In the environment of Kaggle, the Users are having more perspective and it allows the user to share data sets from one layer to another layer. It is used to provide competitions to solve data science challenges with neural networks. As the NLP (Natural Language Processing) is also a very demandable area where most of the data scientists are used to work. So, if you need to have better exposure to this then it will lead you to a great career as Data Scientist.

Consumer data protection:

1. For any application, the most important prospect is data security. The way through which awareness about data privacy can be made populate to consumers.
2. Most of the Platforms like Facebook and Google, that previously harvested and shared user data freely, have since faced both legal backlash and public scrutiny.
3. Businesses and data scientists will need to navigate legislation.

Need of combating adversarial machine learning:

1. The need for “Adversarial machine learning” is an important area where Data Scientists have to put more effort.
2. When this is taken into consideration, then it enables an attacker to inputs data into a machine learning model with the aim to cause mistakes. So, it provides a way to tackle the facts.
3. An optical illusion is also another important area that is specially designed for a machine for enabling the activity.
4. Data scientists will need to defend against adversarial inputs like this. 

1. N9 IT Solutions is a leading IT development and consulting firm providing a broad array of customized solutions to clients throughout the United States. 
2. It got established primarily with an aim to provide consulting and IT services in today’s dynamic environment.
3. N9 IT also offers consulting services in many emerging areas like Java/J2ee, Cloud Computing, Database Solutions, DevOps, ERP, Mobility, Big Data, Application Development, Infrastructure Managed Services, Quality Assurance and Testing.

Send your profile to resumes@n9-it.com