Data Science with Python Training in Mumbai, India

Mumbai is known for being home to some of India’s most prestigious universities like IIT, Aegis School of Data Science and Cyber Security, Mumbai University etc., that offer data science courses. 

These are the top 8 technical skills needed to become a Data Scientist. These are mandatory for any data scientist to have no matter which city he/she is based in -

• R Programming
• Python coding
• Big Data Hadoop
• Data Visualization
• SQL database and coding
• Machine Learning and Artificial Intelligence
• Apache Spark
• Unstructured data

1. R Programming- Programming based on R language is generally preferred to solve statistical problems. Language R is specifically designed for data science needs. It is extensively used for developing statistical software and data analysis. As it is more user-friendly and performs well in developing graphics modules and statistics, it became a highly-preferred skill for data scientists.
2. Python coding- After JAVA and C/C++, Python is the most common coding language required in data science. Today it is very actively practiced among the active developers and, it has even become essential for some entry-level jobs. Python coding is so versatile that it can be used in almost all the steps of data science.
3. Big Data Hadoop- Hadoop is not a compulsory requirement for Data science, but it is preferred in many projects. Hadoop is used to convey data to various sections of a system or servers. It is required when the volume of the data exceeds the memory of the system, and the rest of the data has to be located by sharing on different servers. 
4. Data Visualization- There are a huge number of data available in raw form in the market. It is the work of a Data Scientist to transcribe these data in the form that others may be able to visualize and understand it quickly. Tools like- ggplot, d3.js and Matplottlib, and Tableau may be helpful in data visualization.
5. SQL Database and coding- SQL is a programming language that assists in carrying out processes like add, delete and extract data from a database. It helps data scientists to access, communicate as well as work on data. MySQL also supports short commands that can save time and decrease the level of technical skills required to perform operations on a database.
6. Machine Learning and Artificial Intelligence- To become a skilled data scientist, one should have thorough knowledge about machine learning and AI. With the growing demand and competition in the market, enterprises are finding the newest and user-friendly ideas to include in their products, and this is giving rise to the application of ML and AI in achieving new heights. Thus, a data scientist should be competent in ML & AI skills.
7. Apache Spark- In recent times, Apache Spark is one of the most popular big data technologies worldwide. Its working is like Hadoop but it works faster than Hadoop. The data science algorithm works faster with Apache Spark. It also makes it possible for data scientists to prevent loss of data in data science. Unstructured data sets can be handled easily with the help of this big data technology.
8. Unstructured Data- Internet is full of unstructured data, and the main job of a data scientist is to proof, sort, analyze and visualize such data in a structured form and present in front of others. Working with unstructured data is the core of a data science job.

The top 5 behavioral traits of a successful Data Scientist are -

• Curiosity – A curious person will always find a way to learn and explore. This attitude helps a data scientist in moving forward without getting bored with their job.
• Clarity – Data Scientists need a clear picture of data. And so professionals should also be clear about their paths and methods of curating and using such data.
• Creativity - A data scientist should be creative enough in finding new ways to accumulate data which is required. Obtaining data is not as easy a job as it looks. It needs several uncalled methods, and a professional should be able to create these methods.
• Skepticism – Although a data scientist needs to be creative, he also needs to be rational with his thoughts.  Despite advancements in technology every data scientist should know the limits of any resources/methods and should not get carried away with his/her own views alone.

There are many benefits to being in the job declared as the ‘Sexiest job of the 21st century’ by Harvard Business review in 2012:

1. High Pay: There is a high demand for a skilled data scientist in the IT and business industry. Compared to the demand, the supply of such skilled employees is much less and that makes it a high paying job. Not only the demand-supply chain but the qualification they possess, also matters and they get paid for it. The average pay in Mumbai is Rs 575,295 per year.
2. Good bonuses: One's loss is another's gain and no company wants to be on the losing side. To keep their highly qualified employees, the company will surely give them many perks from time to time. Data scientists can also expect impressive bonuses.
3. Education: Being a data scientist means, you would be well-educated and might need to have either a Masters or a Ph.D. due to the demand for knowledge in this field. Thus, this knowledge will open various paths for you. Not only can you become an employee in a big company, but you could receive offers to work as a lecturer or as a researcher for governmental as well as private institutions.
4. Mobility: Having in-depth knowledge and experience will give you an upper hand in choosing whether to work as a freelancer or as a full-time employee. Most of the businesses that collect data are located in developed countries and by getting a job there, you will get a high salary that will raise your standard of living.
5. Network: Publishing research papers in international journals, attending tech talks at conferences, and many more such opportunities will help to expand your network of data scientists.

Below are the must-have business skills you need to become a data scientist-

1. Analytic Problem-Solving
2. Communication Skills
3. Intellectual Curiosity
4. Industry Knowledge

• Analytic Problem-Solving – Business needs proper analysis to solve their problems. A data scientist should have such skills to analyze the data that is generated by the business.
• Communication Skills – One of the key responsibilities of a data scientist is to communicate customer analytics and business trends to companies. A data scientist should have good communication skills so that he can properly share his results with the company.
• Intellectual Curiosity- Having intellectual curiosity as a trait is helpful for both the employee and for the company. A person needs curiosity in finding the data, only then, the work will be done efficiently.
• Industrial Knowledge – Last, but not least, this is perhaps one of the most important skills. Having a solid industrial knowledge clears out the idea of what is required and what should be ignored.

Following are the best ways to brush up your data science skills for data scientist jobs:

• Practicing short coding challenges: Regular sessions of practice helps in maintaining focus and finding the solution.
• Boot camps: Boot camps about Python and other languages are the perfect ways to brush up the programming basics. These camps last not more than a week. It gives the chance of getting theoretical and practical knowledge.
• Online courses: These are online courses and introduce some of the latest trends in the industry. These are generally taught by data science experts and help to get in touch with the latest technological trends.
• Certificate courses: Learning new data science courses will provide you with an additional skill set and helps improve your CV significantly.
• Competitions: Participating in competitions like Kaggle etc. help in improving your problem-solving skills.  Additionally, participating in a competition will also increase the value of your CV.

Mumbai is one of the most advanced cities in India. It is home to some of the most prominent universities and leading companies such as Google, S2 Infotech, BookMyShow, Tata CLiQ, CreditMate, JP Morgan Chase & Co, Truebil, etc. which offers data science. As of now, every foresighted company needs data. 

There are several datasets available that you can use for practicing your data science skills. Here we have compiled a list of datasets categorized according to their difficulty level and your expertise level:

• Beginner Level
  • Iris Data Set: Consisting of 4 columns and 50 rows, this dataset is the easiest, most versatile and resourceful dataset. It is a classification problem that is used for pattern recognition. Practice Problem: Using the parameters for predicting the flower’s class.
  • Bigmart Sales Data Set: This dataset from the retail industry contains 12 variables and 85,223 rows. Operations like product bundling, customizations, inventory management, etc. are carried out using business analytics and data science. It is a regression problem. Practice Problem: Predicting the total sales of the store.
• Intermediate Level:
  • Black Friday Data Set: It is a regression problem with 12 columns and 550,069 rows. This will help you understand the shopping experience of millions of customers.Practice Problem: Predicting the total amount of purchase.
  • Human Activity Recognition Data Set: This dataset consists of 561 columns and 10,299 rows which was collected using smartphone recording of 30 people. Inertial sensors were embedded in each smartphone.Practice Problem: Predicting the category of human activity. 
• Advanced Level:
  • Identify the digits data set: This dataset contains 7000 images of 82X28 dimensions each. It includes studying, analyzing, and recognizing each element present in the image.Practice Problem: Identifying the different elements present in the image.
  • Vox Celebrity Data Set: This dataset is for practicing isolating and isolating speech. You will be using audio processing in deep learning. With 100,000 words from 1,251 celebrities, this large scale speaker identification problem was extracted from YouTube videos.Practice Problem: Identifying the voice of the celebrity.

Here are the right steps that you need to follow to become a top-notch data scientist:

1. Getting started: The first step is to choose a programming language. R and Python are the most preferred programming languages used in the field of Data Science.
2. Mathematics and statistics: One must have the skills of mathematics and statistics to analyze the data, decipher patterns in it and figure out the relationship among them.
3. Data visualization: Data visualization is required to make the data understandable for the non-technical members. It is also a great way to communicate with the end users.
4. ML and Deep learning: Machine learning and deep learning skills are needed for creating the tools to perform the analysis of the data.

Below are the right steps to becoming a successful data scientist:

1. Degree/certificate: Mumbai is known for being home to some of India’s most prestigious universities like IIT, Aegis School of Data Science and Cyber Security, Mumbai University etc. You can opt for either online or offline courses. At least, pursue a certification course from a registered training. These classes will be beneficial for your growth and teach you the correct use of methods and tools required in the field of data science. 
2. Power up your math and statistics skills: Data scientists must be able to understand the world of numbers and stats. Knowing and understanding algorithms and statistical methods should be the priority of a data scientist. 
3. Learn to code: Coding is the heart of data science and every person who is engaged in sorting out data should have some knowledge about coding. One should start with learning a coding language. Open-source language like Python is recommended here.
4. Knowing the concept of ML: Machine Learning is linked to the big data and is in high demand in the market. Artificial intelligence algorithms are used by machine learning to turn data into value, without the use of program coding.
5. Understand data visualization: Data visualization is analyzing, sorting, curating and transcription of raw data into such a form that can be understood by the company. To become a data scientist, one should learn these skills and their applications.
6. Understand Database: The data is stored in the database and building up of your own data storage is a massive advantage and skill which can be helpful in your career of being a data scientist.

Mumbai is known for being home to some of India’s most prestigious universities like IIT, Aegis School of Data Science and Cyber Security, Mumbai University etc. These global universities offer top courses and degrees in Data Science. Having a degree shows that you have studied and applied most of the concept of data science before applying for a job. This is the reason why almost 88% of data scientists hold a Master’s degree while 46% of all data scientists are PhD degree holders.

A degree is very important because of the following –

• Networking – When you are a professional, having a wide network becomes an asset for your personal as well as professional growth. While pursuing a degree, you will get the opportunity to make like-minded acquaintances, which will be an aid to your network.
• Structured learning – Getting a degree and formal education in the field of data science is more effective and beneficial than doing things unplanned.
• Internships – Enrolling in a course may help you to get a good internship opportunity. An internship helps to get practical knowledge and experience which is the demand of the companies.
• Required academic qualifications for your résumé – Applying for a job starts from submitting your resume. The most common and prior qualification a company demands on a resume while giving you a job is a formal degree from a recognized institution. A degree from a prestigious institution will not only look good but will also give you a chance to apply for the top jobs.

Knowledge, experience, and capability of a person determines whether they need a master degree or not to become a data scientist. Having a master degree can add value to your resume but it is not always the case. A person can still become a good data scientist without having a master's degree if he excels in other fields, related to data science. Further, having a master degree will add other skills and polish the already existing skills you have. Generally, people go for Master's degree either because they must have come from a different undergraduate program or they want to gain more experience in data sciences.

Knowledge of programming is the most important and basic skill that a data scientist must possess. Other reasons why knowledge in programming is required include:

• Data sets: Data science involves working with large amounts of data sets. Knowledge of programming aids a data scientist in the analysis of large data sets.
• Statistics: It needs programming to do the level of statistics that are needed in data sciences. Good knowledge of programming will enhance the ability to solve the statistical problem in a much easier way.
• Framework: The programming ability of a data scientist also enables him/her to create relevant frameworks that can automatically analyze experiments and visualize data.

A Data Scientist earns an average annual salary of Rs. 6,72,492 in Mumbai.

As opposed to the Data scientist’s average annual salary of Rs. 6,72,492 in Mumbai, Data Scientists in Delhi earn about Rs. 9,92,129 annually.

The average annual earnings of a Data Scientist in Mumbai is Rs. 6,72,492  as compared to Rs. 6,15,496 earned by a Data Scientist in Bangalore.

A Data Scientist in Mumbai earns about Rs. 6,72,492 every year as compared to Rs. 8,19,815 earned by a Data Scientist in Chennai.

The average annual salary of a Data Scientist in Mumbai is Rs. 6,72,492. While the same in Pune, a major city in Maharashtra, is Rs. 5,89,581.

The demand for a Data Scientist in Mumbai is high. Every company produces data on a daily basis and they require trained professionals who can analyze this data for business continuity. The demand for a data scientist is far more than the supply and it’s not going to go down anytime soon.

The primary benefit of working as a Data Scientist in Mumbai is that the city offers so many job opportunities. With plenty of companies embracing big data to help them make important business decisions, the importance of Data Scientists has increased. So higher salaries, better perks and more opportunities can be listed as some of the benefits of being a data scientist in Mumbai.

For a Data Scientist, Mumbai is one of the best cities to work in. There are a number of companies that are looking to invest in Data Science and are looking for Data Scientists to convert their raw numbers into insights. Also, a data scientist doesn’t have to stay bound to a particular field. They can choose a field of their interest because today every company in every field is investing in Data Science. Being one of the major cities in the country, it has a number of data science events organized daily where you can meet fellow data scientists and build your network. 

If you are a data scientist in Mumbai, the companies where you can look for job opportunities include BlackRock, Colgate, Palmolive, Google, Prognoz Technologies Pvt. Ltd., Adoro, BookMyShow, General Mills, Spheno, Cymetrix Software, Accrete.AI, Ketto, Camsdata, Bureau Veritas India, Weatherford and many more. 

1. Gartner Data & Analytics Summit 2019, Mumbai

• About the conference: The conference will have a discussion on Analytics and how it can bring clarity in a world of ambiguity. 
• Event Date: 10th - 11th June, 2019
• Venue: Renaissance Mumbai Convention Centre Hotel, 2 & 3B, Near Chinmayanand Ashram, Powai, Mumbai, Maharashtra 400087
• Days of Program: Two
• Timings: 7:15 AM - 8:00 PM
• Purpose: Develop a foundation of efficient business, running through data quality, security, governance and privacy.
• Number of speakers: 20+
• Speaker's profile: 
• Rita Sallam, Research VP, Gartner 
• Ted Friedman, Vice President and Distinguished Analyst, Gartner Research 
• Ehtisham Zaidi Sr Principal Analyst, Gartner 
• Whom can you Network with in this Conference: Gartner Chief Digital Officer (CDO) Circle, End-user case studies, analyst-user roundtables and Gartner one-on-one meetings.
• Registration cost: Standard Conference Fee - INR 65,000 + Taxes and Public-Sector Rate - INR 52,500 + Taxes
• Who are the major sponsors: IBM, Qlik, SAP, CloudEra, Cognizant, NxtGen, etc.

2. The MachineCon, 2019, Mumbai

• About the conference: The Machine Conference is an exclusive setting for Analytics and Data Science Leaders of Asia. The agenda is to examine the best opportunities in a data powered world.
• Event Date: 24th May, 2019
• Venue: Novotal Juhu, Mumbai
• Days of Program: One
• Timings: 8:00 AM - 6:30 PM
• Purpose: The theme of the conference is ‘Put Analytics to work.’ The aim is to create a compelling case of utility for Data Analytics and its various benefits.
• Number of speakers: 20+
• Speaker's profile: TBA
• Whom can you Network with in this Conference: Colleagues and dedicated industry professionals from all over the country. 
• Registration cost: INR 25,000
• Who are the major sponsors: Analytics India Magazine

3. Data Workshop and Meetup, Pydata initiative, Mumbai 

• About the conference: The conference will bring together data scientist and Python experts to discuss improvements in the business. 
• Event Date: Saturday, May 18, 2019
• Venue: 91springboard Vikhroli, Opposite Vikhroli Bus Depot, Vikhroli West, Mumbai
• Days of Program: One
• Timings: 3:00 PM to 7:00 PM
• Purpose: Discussion around the scope of architecture implemented by attention and implementation of basic OCR using pytesseract. 
• Number of speakers: One
• Speaker's profile: Aatish Patel, Deep Learning Researcher at NanoNets
• Whom can you Network with in this Conference: Learners and coaches of Python, Deep Learners, Tensorflow and neural networkers. 
• Registration cost: Free Entry 
• Who are the major sponsors: NumFOCUS, 91 Spring Board, Rise Mumbai 

4. DataGiri's Code-along Saturdays, Mumbai

• About the conference: DataGiri's code-along brings incredible opportunity to avail hands-on experience on a wide range of data science skills at an 8-hour workshop. 
• Event Date: 11th May, 2019
• Venue: TBA
• Days of Program: One
• Timings: 10:00 AM onwards
• Purpose: A deep look into Data Science by the top Analytics professionals in the industry, followed by an hour-long networking with the leaders in Data Science. 
• Number of speakers: One 
• Whom can you Network in this Conference: Professionals and top data scientists 
• Registration cost: Free Entry

5. Deep Learning with Computer Vision in FinTech, Mumbai

• About the conference: Deep Learning with Computer Vision in FinTech presents you with a great chance to employ more practises on Deep Learning and Computer Vision. 
• Event Date: Saturday, May 11, 2019
• Venue: Rise Mumbai 1902, 19th floor Tower B, Peninsula Business Park, Lower Parel, Mumbai
• Days of Program: One
• Timings: 2:30 PM to 5:30 PM
• Purpose: Learn best practices on Deep Learning and Computer Vision
• Whom can you Network with in this Conference: Database Administrators, Database Developers, Business Intelligence officials and many other career professionals.
• Registration cost: Free Entry
• Who are the major sponsors: GreyAtom and RiseMumbai.

6. Machine Learning - A Graphical Intuition, Mumbai

• About the conference: The session provides deep insight into the promising careers in Data Science.
• Event Date: Sunday 12 May, 2019
• Venue: CETTM - Center for Excellence in Telecom Training and Management, MTNL Technology Street, Hiranandani Gardens, Powai, Mumbai, Maharashtra 400076
• Days of Program: One
• Timings: 11:00 AM – 12:30 PM IST
• Purpose: Get answers to all your queries pertaining to a promising career in Data Science.
• Number of speakers: One
• Speaker's profile: Dr. Varadharajan - Professor - INSOFE
• Whom can you Network in this Conference: Vibrant youth from all over the country who are data science enthusiasts.
• Registration cost: Free Entry

7. IDF Mumbai Online Meetup, Mumbai

• About the conference: IDF Mumbai India is a gathering of user experience designers, interaction designers, and information architects.
• Event Date: May 17, 2019
• Venue: Online
• Days of Program: One
• Timings: TBA
• Purpose: A session of conversations, meetups, and other engagements with important members of data community.
• Whom can you Network with in this Conference: Data scientists, specialists and other professionals. 
• Registration cost: Free Meetup

8. The Fifth Elephant Winter 2019, Mumbai

• About the conference: The conference will cover data engineering, data governance including data quality, version control and trust in data, and workflows in organizations, leveraging data for business use cases, optimizing analytics with innovations and tooling and inculcating analytical thinking in teams and organizations.
• Event Date: Friday, 18th Jan, 2019
• Venue: ISDI ACE, Colab Area, 7th Floor, Tower 2A, One India Bulls Center, Lower Parel, Mumbai, Maharashtra - 400013
• Days of Program: One
• Timings: 9:30 AM - 5:20 PM 
• Number of speakers: Four
• Speaker's profile: 
• Kumar Puspesh, CTO & Co-Founder, Moonfrog
• Govind Pandey, Senior Engineering Manager, Flipkart
• Kaushik Bhatt, Vice President
• Vekata Pingali, Co-Founder and CEO, Scribble Data.
• Whom can you Network in this Conference: Product developers, Data Scientists, Engineers and experts. 
• Registration cost: Not Disclosed 
• Sponsors: ISME, Elastic, Trusting Social Engineering, etc.

9. Asian Conference on Recent Advances in Science, Engineering and Technology, Mumbai 

• About the conference: Asian Conference on Recent Advances in Science, Engineering and Technology is a prestigious event organized to provide an excellent international platform for academicians, researchers, engineers, industrial participants and budding students around the world to SHARE their research findings with the global experts.
• Event Date: 2 May, 2019
• Venue: Radisson Mumbai Goregaon, Mumbai, India
• Days of Program: One
• Timings: 09:00 AM- 06:00 PM
• Purpose: The purpose of the event is to provide an opportunity for global participants to share their ideas and experience with professionals expected to join from different parts of the world. 
• Number of speakers: TBD 
• Speaker's profile: TBD 
• Whom can you Network with in this Conference: Academicians, engineers, researchers, budding students and industrial participants. 
• Registration cost: TBD 

10. India IOT SUMMIT 2019, Mumbai

• About the conference: IoT aims to establish connections between devices, accessories, people, and events in a smooth way. The summit's objective is to provide models of ease to the consumers. 
• Event Date: 8th Feb 2019 
• Venue: Hotel ITC Maratha, Mumbai
• Days of Program: One
• Timings: 8:30 AM - 5:00 PM
• Purpose: Sponsoring or exhibiting at “IOT Summit 2019” is an excellent way to promote your business to a highly targeted group of key decision makers with a specific interest in Iot products and Iot solutions in India.
• Number of speakers: 30
• Key Speaker's profile: 
• Anand Bhangaonka, SVP Head-R&D & SQE - Piaggio Group
• Achin Sharma, Head, Global IT - Royal Enfield
• Shaffic Ahamed, VP & Country Manager IT - Sandvik
• Whom can you Network with in this Conference: Chief Information Officers, Head Engineers, Chief Technology Officers and other career experts.
• Registration cost: Not Disclosed
• Sponsors: Ignitarium, Easy Reach, COI - IOT, etc.

1. Data Science Congress 2018, Mumbai

• About: The science congress conference highlighted the significance of Big Data, Machine Learning, Cognitive Computing and IoT in organizations. It was an important conference for every budding Data Science patriots and Data Science professionals.
• Event Date: 29/05/2018 - 1/6/2018 
• Venue: CIDCO Convention Centre, Mumbai 
• Days of Program: Three
• Timings: 9:00AM - 6:00PM
• Registration cost: INR 5000

2. Data Visualisation Summit, Mumbai

• About: Unicom organized one-day Event on Data Visualization in Mumbai. It was designed through thorough research by industry experts. It also provided great opportunities to establish interactions between some of the biggest brains of the data industry.
• Event Date: September 01, 2017
• Venue: The Lalit, Mumbai, Sahar Airport Road, Andheri East, Mumbai.
• Days of Program: One
• Timings: 8:45 AM - 5:15 PM
• Purpose: The main purpose of this event was to pool together thought leaders, data visualizers, and industry professionals.
• Speaker Profile:
  • Vasuprad Kanade, Associate Director, Accenture
  • Cyrus Lentin, CEO & CTO, MaexaData
  • Sabrina Shaikh, Anayltics Manager, Maersk
• Registration cost: INR 9000
• Who were the major sponsors: 
  • Datanami
  • Datavail
  • Gerrard Consulting
  • UNICOM   

3. Gartner Data & Analytics, Summit 2017, Mumbai 

• About: It was a two-day action-packed conference presenting four tracks of hard-hitting content and developments in the field of data science. 
• Event Date: 6-7 June 2017
• Venue: Renaissance Mumbai Convention Centre Hotel, #2 & 3B, Near Chinmayanand Ashram, Powai, Mumbai
• Days of Program: Two
• Timings: 8:00 AM onwards
• Purpose: The purpose was to build and execute data strategy effectively, empower organization and prepare for fast-moving trends such as machine learning and Hadoop.
• Speaker Profile:
  • Ted Friedman, VP Distinguished Analyst
  • Rita L. Sallam, Research VP and Margaret Heffernan, Entrepreneur, Chief Executive, and Author
• Registration cost: Standard price: INR 54,500 plus taxes, Public sector price: INR 44,000 plus taxes
• Who were the major sponsors:
  • Yellowfin
  • Intellicus
  • Qlik 

4. India IoT Summit 2017, Mumbai

• About: The India, IoT Summit featured a CEO Panel talk on the establishment of IoT in India and the influx of Big Data and customer experience with IoT.
• Event Date: August 22-23, 2017
• Venue: The Lalit, Sahar Airport Rd, Navpada, Marol, Andheri East, Mumbai, Maharashtra
• Days of Program: Two 
• Timings: 3:00 PM onwards
• Purpose: The LTI aimed to showcase its key solutions and offerings across the IoT spectrum. 
• How many Speakers: Four
• Speaker Profile:
  • Sudip Mazumder, Deputy Head – Digital, L&T Construction
  • Sachin Vyas, Head – Mosaic Practice, LTI, etc

Below are the steps you should follow to get a job as a Data Scientist.

1. Getting started
2. Mathematics
3. Libraries
4. Data visualization
5. Data preprocessing
6. Machine Learning and Deep Learning
7. Polishing skills

• Getting started: First step is to choose a programming language. Considering the recent scenario, we suggest you learn Python or R language. 
• Mathematics and statistics: Data science involves a large number of raw data that are present in the unstructured or raw form. Here mathematics as well as statistics, help to sort out this data and present it in a user-friendly way.
• Libraries: Data science process involves various tasks ranging from preprocessing the data given to plotting the structured data and finally to applying ML algorithms as well. Some of the famous libraries include Scikit-learn, NumPy, Pandas, ggplot2 and Matplotlib, etc.
• Data visualization: It’s the job of a data scientist to convert data in such a form that the company can use it. Knowing and presenting the data in a form of graphics or other methods is the ultimate responsibility of a data scientist. The most popular way to visualize data is by creating a graph. Various libraries can be used for this task:
  • Matplotlib – Python
  • Ggplot2 - R
• Data preprocessing: Unstructured data needs to be processed by the data scientists to make it analysis-ready. Many engineering variables help in doing the processing. This processing is done to convert the data to a structured format so that it can be used in the ML tool for analysis.
• ML and Deep learning: Having skills in big data, deep learning and machine learning area is a must-have for every data scientist right now. Deep learning is highly-preferred among data scientists as they have to deal with a huge set of data.
• Polishing skills: Competitions like Kaggle etc. provide an important platform for the budding as well as the established data scientist. Projects and research work also help in polishing the skills, making you better in the league.

 Here is what you need to prepare for a job as a data scientist:

• Study: Make sure that you have an in-depth knowledge of topics like Probability, statistics, statistical models, machine learning, and neural networks.
• Meetups and conferences: You need to build your professional network by visiting data science conferences, meetups and tech talks. This will help you with referrals in the future.
• Competitions: For brushing up your data science skills, you can participate in online competitions like Kaggle.
• Referral: Referrals are a great source of getting interviews. Your LinkedIn profile needs to be updated and maintained.
• Interview: Once you feel like you are ready, you can start giving the interviews. You might have to get through a couple of interviews before you land a job. What you need to do is learn from your mistakes and study better for the next interview.

The major roles and responsibilities of a Data Scientist include the following:

• Collect the data that is required to meet the needs of the business. This data will be mostly in the unstructured form.
• After this, you need to extract the relevant data from the huge data and organize it.
• Next step is creating machine learning tools, techniques and programs for analyzing the data.
• Lastly, statistical analysis is performed for gathering insights and predicting future outcomes.

The average salary for a Data Scientist is Rs 10,34,432 in Mumbai, India. 

https://www.glassdoor.co.in/Salaries/mumbai-data-scientist-salary-SRCH_IL.0,6_IM1070_KO7,21.htm 

The Data Science career path is as follows:

Business Intelligence Analyst: A business intelligence analyst is responsible for figuring out how the business works and how the market trends affect it. They perform data analysis to get a clear picture of the current standing of the business.                                                                   

Data Mining Engineer: A data mining engineer examines the data and creates the algorithm required for data analysis.

Data Architect: A data architect is responsible for creating blueprints used to integrate, centralize, maintain, and protect the data sources. They work with system designers, developers and users to do the same.

Data Scientist: A Data Scientist analyzes the data, creates a hypothesis, and explores the patterns in the data. They also develop algorithms and systems that provide insights from raw data.

Senior Data Scientist: A senior data scientist makes sure that all the future projects, systems and data science are shaped in a way to fulfill the needs of the business.

Some renowned associations and groups of data scientists are:

• Mumbai Artificial Intelligence & Deep Learning
• Data Science community in Thane
• Mumbai Big Data Analytics Meetup
• Aegis-IBM Data Science, Big Data, Analytics, AI, ML, DL
• Love Data Science - Live Data Science
• Driven by Data - IBM Storage Mumbai
• Data Science Mumbai
• Data Science Hub

 Here is how you can network with other data scientists:

• Social gatherings like Meetup
• Data science conference
• An online platform like LinkedIn

It has been seen that the demand for data science jobs has been increased by 15% which was 12% last year in Mumbai. Right now, with huge demand, there are several career options due to organizations like Google, S2 Infotech, BookMyShow, Tata CLiQ, CreditMate, JP Morgan Chase & Co, Truebil, etc, searching for a data scientist in Mumbai:

• Business Intelligence (BI) Developer
• Data Architect
• Applications Architect
• Infrastructure Architect
• Data Scientist
• Machine Learning Scientist
• Data Scientist
• Business Analyst
• Marketing Analyst
• Data/Analytics Manager

Here are the tools and software that you need to master to be preferred over other data scientists by the employers:

• Education: A degree in Data Science will jumpstart your Data Science career. You can also try getting some certifications.
• Programming: You need to be an expert in programming. Start with the basics and then learn about the data science libraries.
• Machine Learning: Machine learning and deep learning skills help in creating tools and frameworks required for performing the data analysis.
• Projects: Take on as many real-world projects as you can. This will improve your data science skills and improve your portfolio.

Python is highly preferred by data scientists over other programming languages due to its simplicity and the dedicated packages and libraries made particularly for data science use. It gives data scientists access to a broad range of resources, which helps them solve problems that may come up during the development of a Python program or Data Science model. 

 Here are the 5 most popular programming languages used for Data Science:

•  R: Although R is difficult to learn, it offers certain advantages that make it perfect to be used in the field of Data Science. Firstly, there are several high quality and open source packages offered by its global community. You can also try data visualization with R using ggplot2. Lastly, it has several statistical functions that help in processing complex matrix operations. 
• Python: Python is the most commonly used and preferred programming language in the field of data science. It is because it has a syntax that is similar to English language that makes it easy to read, write, and understand. There are several python libraries like Pandas, tensorflow, and scikit-learn that are used for data science projects. It also has the support of its global, open-source community.
• SQL: You need to have knowledge of SQL to work with databases that includes querying, updating, and manipulating. It also has a very easy syntax.
• Java: Despite its limited verbosity and libraries, Java is used in Data Science projects because it is a compiled, general purpose, high-performance language which is compatible with several systems. This is because there are already systems in place with its backend coded in Java.
• Scala: This language is used in several data science projects. It has a difficult syntax. But since it runs on JVM, it makes it compatible with Java. When used with the Apache Spark framework, it offers high-performance cluster computing.

Here is how you can download and install Python 3 on Windows:

• Download and setup: Visit the download page and use the GUI installer to setup Python on your windows. Make sure that while you are installing, you select the checkbox asking to add Python 3.x to PATH. This is your classpath that will allow you the usage of Python's functionalities from the terminal. 

You can also use Anaconda to install Python. If you want to check if Python is installed, you can try using the following command that will show the current version of Python installed:

python --version

• Update and install setuptools and pip: If you want to install and update the crucial libraries, you can use the following command:

python -m pip install -U pip

Note: You can create isolated Python environments and pipenv using virtualenv. Pipenv is a Python dependency manager. 

For installing Python 3 on Mac OS X, you can either simply install the language from their official website using a .dg package or use Homebrew python or its dependencies. Here are the steps you need to follow:

• Install Xcode: First, you need to install Xcode. You will need the Xcode package of Apple/ Start using the following command: $ xcode-select --install
• Install brew: Next, you have to install Homebrew which is a package manager for Apple. Start with the following command: 

/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)" Confirm if it is installed by typing: brew doctor

• Install python 3: Lastly, to install python, use the following command: 

brew install python

• If you want to confirm the version of python, use the command: python --version

You should install virtualenv that will create isolated places for you to run different projects and can even run different versions of Python on different projects.