How To Begin My Career in Data Science as a Fresher

Data Science has a career that involves a combination of data handling, modeling and presentation skills. To start a career in data science some of the prerequisites you must have such as strong stuff on Mathematical concepts like statistics, probability, and linear algebra and the basic knowledge of programming languages like R or Python also with the fundamentals of SQL Connections.

Other than this, there are some important things for a student to be observed to begin a career in Data Science. Eight of them explained here that are taken into higher consideration.

Choose the Right Role

There are a variety of choices to be selected in the data science industry. According to the interest level and education background, it is best to get into the opt role. Some major job roles and responsibilities are mentioned below that are ruling the Data science industry with high demand

Data Visualization Expert:

• Develop new User-Facing features
• Build reusable code and libraries for future use
• Ensure the technical feasibility of UI/UX designs
• Optimize application for maximum speed and scalability
• Ensure that all user input is tested before submitting to back-end
• Collaborate with other team members and stakeholders

Machine Learning Expert:

• Design and Develop Machine Learning, Analytical Methods, and Novel Algorithms
• Perform Exploratory Data Analysis
• Generate and Test working hypothesis
• Prepare and analyze historical data and identify patterns
• Provide Technical Support for management and business customers
• Manage the community with the knowledge sharing

Data Scientist:

• Building and optimizing classifiers using machine learning techniques
• Extending the company’s data with third party sources of information if needed
• Developing data collection procedures to create Analytical Systems
• Processing, Verifying, and Cleansing the ethics of data for analysis
• Process the ad-hoc analysis and present the results
• Creating an automated anomaly detection system and keep on tracking its performance

Data Engineer:

• Selecting and integrating any Big Data tools and frameworks needed to give requested capabilities
• Implementing the ETL Process
• Monitoring performance and advising any necessary infrastructure changes
• Defining data retention policies
• And many more to know before choosing a role. And it is better to don’t be hurry to jump into a role and clearly understand the requirements of the chosen field and prepare for it.

2.Take up a course and complete it

Once decided on the role, it is very much needed to put dedicated effort to understand the role and its requirements. As the demand for data science is big, the courses and studies related to it also huge in number to get molded.

So choose the course with highly benefited in the area of clear understanding, real-time practices, career guidance, placement assurance and course upgrade facility and so on. While doing course make sure to do assignments, discussions, and coursework in the field. For all the said benefits it is suggested to enroll in any Data Science Training Institute in Chennai instead of sitting and just read out the tutorials at home.

3.Choose a tool/Language

It is very much important to get an end-to-end practice of the chosen course. And it is also mandatory to choose a tool for data science to implement the thoughts and understand the concept thoroughly.

It is to be selected according to the interest and skills in code writing. Preferable of GUI based languages like Python, Java, JavaScript, C++ helps to grasp coding knowledge even if you are not well-versed in coding part.

4. Join a peer group

After choosing a language or tool, it is advisable to join a peer group to get motivated by sharing the current trends and coding assistance when needed. The group can either be a physical or over the internet who shares similar goals and interests and interacting about the course-related pieces of stuff.

Some of the forums are there online to discuss about the technical things like StackExchange, Quora, Analytics Vidhya, and Reddit

5. Focus on practical applications than theory

Focusing on practical experience brings not only course understanding but also the way of application in reality.

Some of the major points to be followed while pursuing the course are mentioned below:

Make sure of doing all the exercises and assignments to understand the application well

Do work on some data sets and apply the concepts even if it is not understandable in the area of math behind the technique, given assumptions, result interpretation.

Go through the solutions given by other people who have worked on it and it helps to find out the correct approach faster

6 Follow the right resources:

Learn about the course continually by reading the blogs related to the course which are run by the top data scientists or the training institutes to get deep knowledge. They are active always and help the followers with their new findings and frequently update their post about the current advancement of the field.

Make a habit of reading about data science every day to get updated in recent updations. And make sure of following the right resources to avoid confusion about the sector

7. Work on communication skills:

One can not get the job just with the technical profound but need to be improved in communication skills too. Because it is even more important to stand out from the crowd and also helpful in working on the field to share the ideas with the teammate about the pinpoint concept of the won findings.

8. Make a network, but do not waste time on it

The entire focus should be on learning. For additional benefits, it is suggested to attend industry events, conferences, and popular meetups near your area. Anyone can help at any stage of your learning. These help to get growing in the field in advance level, updates on the current trends, can have mentor-ship support, and also the best option to get job requirements on top companies to fetch it at the right time.

Final Notes :

The demand for data science is enormous and the companies are ready to invest time and money in data scientists. Therewith it is advised to take the right steps for choosing the career to have exponential growth in the field. To know more about the course, contact Softlogics as we provide the best Data science Training in Chennai.

Interview Question & Answers 2019

                         Data science Interview Question & Answers 

1.What is data science in simple words?

Data science is a field of Big Data geared toward providing meaningful information based on large amounts of complex data. Data science, or data-driven science, combines different fields of work in statistics and computation in order to interpret data for the purpose of decision making.

2.What is data science and why is it important?

Data science is about solving business problems. To anyone still asking is data science important, the answer is actually quite straightforward. It’s important because it solves business problems. … Too often businesses want machine learning, big data projects without thinking about what they’re really trying to do.

3.What is data simple language?

Data especially refers to numbers, but can mean words, sounds, and images. Metadata is data about data. It is used to find data. Originally, data is the plural of the Latin word datum, from dare, meaning “give”.

4.What is the eligibility for data science?

Education – Data scientists are highly educated – 88% have at least a Master’s degree and 46% have PhDs – and while there are notable exceptions, a very strong educational background is usually required to develop the depth of knowledge necessary to be a data scientist.

5.What are the different types of data?

Understanding Qualitative, Quantitative, Attribute, Discrete, and Continuous Data Types. At the highest level, two kinds of data exist: quantitative and qualitative. There are two types of quantitative data, which is also referred to as numeric data: continuous and discrete.

6.How do you define a set in Python?

Set in Python is a data structure equivalent to sets in mathematics. It may consist of various elements; the order of elements in a set is undefined. You can add and delete elements of a set, you can iterate the elements of the set, you can perform standard operations on sets (union, intersection, difference).

7.Can you iterate through a set Python?

Iterate over a set in Python. In Python, Set is an unordered collection of data type that is iterable, mutable and has no duplicate elements. There are numerous ways that can be used to iterate over a Set. … Some of these ways include, iterating using for/while loops, comprehensions, iterators and their variations.

8.Why list is mutable in python?

You have to understand that Python represents all its data as objects. … Some of these objects like lists and dictionaries are mutable , meaning you can change their content without changing their identity. Other objects like integers, floats, strings and tuples are objects that can not be changed.

9.What is hashable Python?

From the Python glossary: … All of Python’s immutable built-in objects are hashable, while no mutable containers (such as lists or dictionaries) are. Objects which are instances of user-defined classes are hashable by default; they all compare unequal, and their hash value is their id() .

10.Are sets ordered?

The Set Interface. A Set is a Collection that cannot contain duplicate elements. It models the mathematical set abstraction. … LinkedHashSet , which is implemented as a hash table with a linked list running through it, orders its elements based on the order in which they were inserted into the set (insertion-order).

11.How do you add an element to a set in Python?

set add() in python. The set add() method adds a given element to a set if the element is not present in the set. Syntax: set.add(elem) The add() method doesn’t add an element to the set if it’s already present in it otherwise it will get added to the set.

12.Is Python necessary for data science?

Python is the most common coding language I typically see required in data science roles, along with Java, Perl, or C/C++. Python is a great programming language for data scientists. This is why 40 percent of respondents surveyed by O’Reilly use Python as their major programming language.

13.Is Python enough for data science?

R and Python are the two most popular programming languages used by data analysts and data scientists. Both are free and open source – R for statistical analysis and Python as a general-purpose programming language. Excellent range of high-quality, domain specific and open source packages.

14.How long does it take to learn Python for Data Science?

To learn all the concepts it would take you about two weeks (assuming you study two hours a day and assuming you know a little python ) but then that is not enough because you would only know how to use those concepts with experimentation and practice which is never enough.

15.What should I study to become a data scientist?

There are three general steps to becoming a data scientist: Earn a bachelor’s degree in IT, computer science, math, physics, or another related field; Earn a master’s degree in data or related field; Gain experience in the field you intend to work in (ex: healthcare, physics, business).

16.Which is better Python or R for data science?

In a nutshell, he says, Python is better for for data manipulation and repeated tasks, while R is good for ad hoc analysis and exploring datasets. … R has a steep learning curve, and people without programming experience may find it overwhelming. Python is generally considered easier to pick up.

17.What is SAS in data science?

Tech and Telecom companies require huge volumes of unstructured data to be analyzed, and hence data scientists use machine learning techniques for which R and Python are more suitable. SAS is an expensive commercial software and is mostly used by large corporations with huge budgets.

18.Which language is best for data science?

The Most Popular Languages for Data Science

Python. Python is at the top of all other languages and is the most popular language used by data scientists…R. R has been kicking around since 1997 as a free alternative to pricey statistical software, such as Matlab or SAS…Java….

Scala.

19.Is Java necessary for data science?

If you’re starting out to build up your application from the ground level, it’s good to choose Java as your programming language. Java is Fast: Unlike some of the other widely used languages for Data Science, Java is fast. Speed is critical for building large-scale applications and Java is perfectly suited for this

20.Does data scientist need to know programming?

Data scientists usually have a Ph.D. or Master’s Degree in statistics, computer science or engineering. … Programming: You need to have the knowledge of programming languages like Python, Perl, C/C++, SQL and Java—with Python being the most common coding language required in data science roles.

21.Which language is better for data science?

Both Python and R are popular programming languages for statistics. While R’s functionality is developed with statisticians in mind (think of R’s strong data visualization capabilities!), Python is often praised for its easy-to-understand syntax.

22.How is Python used in data science?

Pandas is the Python Data Analysis Library, used for everything from importing data from Excel spreadsheets to processing sets for time-series analysis. … SciPy is the scientific equivalent of NumPy, offering tools and techniques for analysis of scientific data. Statsmodels focuses on tools for statistical analysis.

23.What does data science mean?

Data science is 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, similar to data mining.

24.Is Data Science easy?

Data science is easy if you have the right data scientists. I am not in any way saying that the complex discipline known as data science is easy or that becoming a proper data scientist is simple. … If you get them the data, they can create a model that delivers value where there is value to be had.

25.What is data science with example?

A common question among directors, managers and the C-suite is what are some examples of business cases using data science. Data science is a tool that can be used to help reduce costs, find new markets and make better decisions.

26.Is Data Science in demand?

Data scientists are expected to know a lot — machine learning, computer science, statistics, mathematics, data visualization, communication, and deep learning. … I scoured job listing websites to find which skills are most in demand for data scientists.

27.What is data science with Python?

Pandas is the Python Data Analysis Library, used for everything from importing data from Excel spreadsheets to processing sets for time-series analysis. … SciPy is the scientific equivalent of NumPy, offering tools and techniques for analysis of scientific data. Statsmodels focuses on tools for statistical analysis.

28.What is data science with R?

It’s many things: R is data analysis software: Data scientists, statisticians, and analysts—anyone who needs to make sense of data, really—can use R for statistical analysis, data visualization, and predictive modeling. … R’s open interfaces allow it to integrate with other applications and systems.

29.What does a data science do?

“More generally, a data scientist is someone who knows how to extract meaning from and interpret data, which requires both tools and methods from statistics and machine learning, as well as being human. She spends a lot of time in the process of collecting, cleaning, and munging data, because data is never clean.

30.Why is data science important?


Data Science can do more than that. Data Science helps humans make better decisions; either quicker decisions or better decisions. Companies invest a lot of money in data science so they could get the right information to make the right decisions.


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Data Science for the aspiring data scientist in 2019

How does it feel to know data science for the aspiring data scientist in 2019?

Data science encompasses various topics. This comprises AI. Machine Learning, IoT amongst others. If you wish to develop your career in data science, having a data science course in Chennai will be beneficial. 

Through data science, industries are in a position to evaluate trends in the market, perform accurate decisions, and also assess the potential risks. The mitigation of losses by sectors is one of the critical points of data science. Thus there is an increase in the demand for data scientists. 

Data science is a budding field

Data science is still in its inception stage. Hence, people have to get the hang of it. However, if you are expert in this domain, then the companies will recruit you with handsome pay. As said earlier, the maximization of profits is the primary concern of the companies. The data scientist can derive useful insights from the data. The knowledge of data science tools will also be helpful in this regard. With the ideas obtained, the data scientist will help in predicting the future. 

Which programming language to choose for data science?

There is a lot of debate going on as to whether R or Python is the best programming language for data science. Python is mostly considered appropriate because it has a simple learning curve, and it consists of a large section of libraries. 

Python for Data Science 

Professionals functioning with data science want a hassle-free way of handling programming techniques. Thus, they select Python, which has a simple syntax. The developments become much swift with the help of Python. To know more, enroll in the best data science course in Chennai. 

Data science comprises extrapolating useful details from vast sets of statistics and data. These data are not appropriately sorted, and hence, there is a complication to bring out sound accuracy. Python comes to the rescue here by being a general-purpose programming language. There is the advantage of CSV output for simple reading of data in a spreadsheet. Besides, if data cleaning is needed, then Python is the right choice. 

The open-source nature and flexibility of Python also add to its popularity in data science. Besides, Python can easily integrate with the available infrastructure and can fix complicated problems. These are some of the reasons why data scientists prefer Python. 

R for Data Science

R is widely favored by data miners and statisticians for data evaluation and developing statistical software. This free to use language is suitable for Econometrics in data science. R can also generate business-ready infographics, reports, etc. Besides, it consists of a robust infrastructure, which makes it an excellent choice for data scientists. Though R had a steeper learning curve earlier, it is becoming less steep thanks to the introduction of TidyVerse. This package offers a consistent structural programming interface. There is also the presence of a streamlined syntax in R for building visualizations. Once you join the data science training in Chennai, you will master data science with R. 

NoSQL for data science

We can perform a significant number of things with unstructured data. We can apply it to classify sentiments on social media posts or carry out natural language processing.     NoSQL is outstanding at storing this form of scraped data. NoSQL makes it simpler to quickly accumulate vast sets of data and promptly scale data stores to meet demand. 

Conclusion

Data science is a vast concept, and there are several jargons attached to it. When you google for the data science terms, you would be wondering whether to really become an expert in every concept. Data science trends are also ever changing. Now the buzz is learning data science with Python, R or machine learning. For further clarification, you can enroll in the data science training in Chennai and take your career to the next level. In fact, learning data science can be a satisfying feeling because you are taking up a challenging position. The organizations will consider you as an asset once you prove your skills in data science. 

Data Science Training in Chennai

                                                Data Science Training in Chennai

Top reasons to learn Data science 

In the present data-driven world, data science has turned out as an exciting and expanding field. The requirement for data science training in Chennai is felt more than ever. Well, what do these data scientists do? They work on a massive sum of data and process it such that it is beneficial for organizations. Now let's see some of the reasons for learning data science:

Excellent job opportunities

The demand for data scientists is shooting. However, there’s a substantial shortage on the supply side. There are a lot of unfilled job positions across the world because of the lack of needed skill sets. The concern is that the candidate should possess good experience in coding, statistics, scientific query for data science roles. They should have the skills to comprehend the business problem, statistics knowledge to evaluate the data rigorously, and proficiency to code whatever is needed to execute the solution. To apply the knowledge of data science in practice, it becomes essential to take up the best data science training course in Chennai. 

Quick growth

Data science is the domain that is gaining popularity across industries, and it is not going to fade sooner. In your role of a data scientist, you would be performing research and evaluation to find answers to issues and assist the organization to make informed decisions.

Varied working exposure

When you are a data scientist, you can search for a diverse spectrum of domains. E-commerce businesses, prosecution companies, renewable energies, and even startups are the right choice. 

You will work on intelligent things

Organizations generally contact data scientists concerning taking business decisions. You may even carry out a smart evaluation to present your findings. It is an excellent thing if you are discovering something significant. Besides, at its heart, learning data science allows you to become a data-driven thinker. You will be carrying out informed findings from a plethora of information from varied sources. This job profile assists you make a sound assessment in every role you perform. 

You will learn varied skills

Data visualization, coding, predictive modeling, etc., are some of the essential skills that you will learn. Moreover, you will also be skilled in statistics and probability. Join the Best data science course in Chennai and learn all these concepts. 

Analyzing at a deeper level makes a data scientist shine

Concerning difficult questions and hypotheses, some person has to explore more and make out things at a deeper level. They have to evaluate and explore the issues thoroughly. Data scientists are the ideal candidates here. 

Role of Python and R in data science

Python is the most frequently used coding language, and it is needed in data science roles besides Java, C/C++, or Perl. Python has the reputation of being an excellent programming language for data scientists. Due to its versatility, you can apply Python for most of the steps needed in data science processes. However, you needn’t be a Python specialist, to begin with data science. Python scripting skills are sufficient. You can learn data science with Python from the best data science training in Chennai. 

Concerning R, it is framed explicitly for data science needs. You can apply R to solve any issue you face in data science. You can learn data science with R from the best data science training course in Chennai. 

Learn the most famous data science tools

Data science is consistently evolving, and data scientists are always applying new and innovative tools to make their jobs more competent. When you enroll in the data science training in Chennai, you can learn all of the critical data science tools that are applied today. Different companies use different tools, so it is essential to learn all the tools. You should not only learn about the data science tools but also the programming tools which will help in your job as a data scientist. 

Are you prepared to shine in the competition and make a great impression on potential employers? Do you want to prove your expertise in data science but pondering over where to join? Then it’s the right time to enroll in the data science training in Chennai and take your career to the next level.

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