Data Science Course with Python in Pune, India

The Data Science with Python course has been thoughtfully designed to make you a dependable Data Scientist ready to take on significant roles in top tech companies. At the end of the course, you will be able to:

• Build Python programs: distribution, user-defined functions, importing datasets and more
• Manipulate and analyse data using Pandas library
• Data visualization with Python libraries: Matplotlib, Seaborn, and ggplot
• Distribution of data: variance, standard deviation, interquartile range
• Calculating conditional probability via Hypothesis Testing
• Analysis of Variance (ANOVA)
• Building linear regression models, evaluating model parameters, and measuring performance metrics
• Using Dimensionality Reduction Technique
• Building Binomial Logistic Regression models, evaluating model parameters, and measuring performance metrics
• Building KNN algorithm models to find the optimum value of K
• Building Decision Tree models for both regression and classification problems
• Build Python programs: distribution, user-defined functions, importing datasets and more
• Manipulate and analyse data using Pandas library
• Visualize data with Python libraries: Matplotlib, Seaborn, and ggplot
• Build data distribution models: variance, standard deviation, interquartile range
• Calculate conditional probability via Hypothesis Testing
• Perform analysis of variance (ANOVA)
• Build linear regression models, evaluate model parameters, and measure performance metrics
• Use Dimensionality Reduction
• Build Logistic Regression models, evaluate model parameters, and measure performance metrics
• Perform K-means Clustering and Hierarchical Clustering
• Build KNN algorithm models to find the optimum value of K
• Build Decision Tree models for both regression and classification problems
• Build data visualization models for Time Series data and components
• Perform exponential smoothing

The program is designed to suit all levels of Data Science expertise. From the fundamentals to the advanced concepts in Data Science, the course covers everything you need to know, whether you’re a novice or an expert. To facilitate development of immediately applicable skills, the training adopts an applied learning approach with instructor-led training, hands-on exercises, projects, and activities.

Yes, our Data Science with Python course is designed to offer flexibility for you to upskill as per your convenience. We have both weekday and weekend batches to accommodate your current job.

In addition to the training hours, we recommend spending about 2 hours every day, for the duration of course.

The Data Science with Python course is ideal for:

• Anyone Interested in the field of data science
• Anyone looking for a more robust, structured Python learning program
• Anyone looking to use Python for effective analysis of large datasets
• Software or Data Engineers interested in quantitative analysis with Python
• Data Analysts, Economists or Researcher

There are no prerequisites for attending this course, however prior knowledge of elementary programming, preferably using Python, would prove to be handy.

To attend the Data Science with Python training program, the basic hardware and software requirements are as mentioned below -

Hardware requirements

• Windows 8 / Windows 10 OS, MAC OS >=10, Ubuntu >= 16 or latest version of other popular Linux flavors
• 4 GB RAM
• 10 GB of free space

Software Requirements

• Web browser such as Google Chrome, Microsoft Edge, or Firefox

System Requirements

• 32 or 64-bit Operating System
• 8 GB of RAM

On adequately completing all aspects of the Data Science with Python course, you will be offered a course completion certificate from KnowledgeHut.

In addition, you will get to showcase your newly acquired data-handling and programming skills by working on live projects, thus, adding value to your portfolio. The assignments and module-level projects further enrich your learning experience. You also get the opportunity to practice your new knowledge and skillset on independent capstone projects.

By the end of the course, you will have the opportunity to work on a capstone project. The project is based on real-life scenarios and carried-out under the guidance of industry experts. You will go about it the same way you would execute a data science project in the real business world.

The Data Science with Python workshop at KnowledgeHut is delivered through PRISM, our immersive learning experience platform, via live and interactive instructor-led training sessions.

Listen, learn, ask questions, and get all your doubts clarified from your instructor, who is an experienced Data Science and Machine Learning industry expert.

The Data Science with Python course is delivered by leading practitioners who bring trending, best practices, and case studies from their experience to the live, interactive training sessions. The instructors are industry-recognized experts with over 10 years of experience in Data Science. 

The instructors will not only impart conceptual knowledge but end-to-end mentorship too, with hands-on guidance on the real-world projects.

Our Date Science course focuses on engaging interaction. Most class time is dedicated to fun hands-on exercises, lively discussions, case studies and team collaboration, all facilitated by an instructor who is an industry expert. The focus is on developing immediately applicable skills to real-world problems.

Such a workshop structure enables us to deliver an applied learning experience. This reputable workshop structure has worked well with thousands of engineers, whom we have helped upskill, over the years. 

Our Data Science with Python workshops are currently held online. So, anyone with a stable internet, from anywhere across the world, can access the course and benefit from it.

Schedules for our upcoming workshops in Data Science with Python can be found here.

We currently use the Zoom platform for video conferencing. We will also be adding more integrations with Webex and Microsoft Teams. However, all the sessions and recordings will be available right from within our learning platform. Learners will not have to wait for any notifications or links or install any additional software.

You will receive a registration link from PRISM to your e-mail id. You will have to visit the link and set your password. After which, you can log in to our Immersive Learning Experience platform and start your educational journey.

Yes, there are other participants who actively participate in the class. They remotely attend online training from office, home, or any place of their choosing.

In case of any queries, our support team is available to you 24/7 via the Help and Support section on PRISM. You can also reach out to your workshop manager via group messenger.

If you miss a class, you can access the class recordings from PRISM at any time. At the beginning of every session, there will be a 10-12-minute recapitulation of the previous class.

Should you have any more questions, please raise a ticket or email us at support@knowledgehut.com and we will be happy to get back to you.

With our 100% Satisfaction Guarantee policy, you are assured of the highest standards of quality. At KnowledgeHut, we strive to ensure that your learning experience with us is beyond reproach. However, if for any reason your expectations are not met, we will refund the course fee in accordance with our 100% Satisfaction Guarantee policy.

Yes, you can switch the start date to your Data Science with Python training, with prior notice of at least 24 hrs and subject to availability in the desired batch.

Yes, we have a 100% money-back guarantee in line with our 100% Satisfaction Guarantee policy.

Yes, scholarships are available for students and veterans with grants up to 50% of the course fees.

To avail scholarships for our Data Science with Python course, please get in touch with us at support@knowledgehut.com. The team shall send across the forms and instructions to you. Based upon the responses and answers that we receive, our panel of experts take a decision on the Grant. The entire process could take about 7 to 15 days.

Yes, group discounts are available and apply to groups as small as three (3) participants. The more participants that attend a training course, the greater the discount. By registering in groups, you can typically save up 20% to 30% on the course fee. For more details, please check out upcoming schedules.

Yes, instalment options are available for payment of course fee. To avail the instalment option, please get in touch with us at support@knowledgehut.com. The team will explain how the instalments work and provide timelines for your case.

Typically, the number of instalments vary from 2 to 3, but the full amount must be paid before you complete the course.

A 2012 survey conducted by the Harvard Business Review termed Data Scientist to be the sexiest job in the 21st century. Pune is not only one of the most developed cities in Maharashtra but is also one of the most digitally advanced cities in India. Pune also has several reputed institutions which offer data science courses such as Symbiosis Centre for Information Technology, Aegis School Of Data Science, Savitribai Phule Pune University, Interdisciplinary School of Scientific Computing, IMS Proschool etc. Some other major reasons why data science is popular in cities like Pune are:

• There is an increase in the demand for data-driven decision making. 
• There is also a lack of trained data scientists in Pune. Professionals that are trained properly in data science are getting paid handsomely. 
• In today’s market, data is collected at an alarming rate and this means that the analysis of this data must match this speed.

Data science necessitates an in-depth understanding of coding, theoretical knowledge and hands-on practical experience. Pune welcomes data scientists who possess the following technical skills: 

• Python coding: If you’re looking for a coding language that is versatile and still simple, Python will be the ideal choice. It can take various formats of data and you can easily import SQL tables into your code.
• R programming: It is an open source programming and statistical language used for data analysis, data manipulation and data visualization. 
• Hadoop: Even though the Hadoop platform isn’t a necessity for learning data science, it is used in several data science projects. A data scientist should have the ability to manage data using Hadoop.
• SQL database: SQL ( Structured Query Language ) is a must for Data Scientists to get the data and to work with that data. 
• Machine learning and AI: Having skills in Artificial Intelligence and Machine Learning is a must if you want to pursue a career in Data Science. This requires being familiar with the following concepts:
  • Neural Networks
  • Decision trees
  • Reinforcement learning
  • Logistic regression
  • Adversarial learning
  • Machine learning algorithms, etc.
• Apache Spark: Apache Spark is a data computation software similar to Hadoop and has the added advantage of being one of the most popular data sharing technologies. The only major difference between the two is that Apache Spark is faster.  While dealing with large datasets, Spark helps disseminate data processing. The speed with which it operates adds to its advantages. Apache Spark also has the reputation of reducing the chance of loss of data. 
• Data visualization: A major part of the job of a data scientist is to help visualise the data. It involves communicating their findings effectively through graphical means. It can be done with the help of tools like d3.js, Tableau, ggplot, and matplotlib.

Here are the top traits you must have to stand out in the crowd as a successful Data Scientist-  

• Curiosity – As a data scientist, you will be handling huge amounts of data every day. To do so effectively, you must have an undying thirst for knowledge. 
• Clarity – As a Data Scientist, you will be handling crucial data for corporations and for that, you need to have a sense of clarity. While cleaning up data sets or writing new codes, you should always know why you’re doing something.  
• Creativity – To get the right results, you need to find links between data while simultaneously finding ways to creatively visualise data. If you can’t figure out what needs to be kept and what needs to go, you won’t be able to get the right results. 
• Skepticism – Data Scientists need to be skeptical, unlike other creative artists. Since you’ll be dealing with real data, you can’t get carried away and need to keep a check on your creativity.

Data science comes with its own bonuses some of which are discussed below.

1. Data scientists are among the highest-paid IT specialists in the business today. What’s more, the demand for Data Science jobs is also pretty high 
2. Be it banking or healthcare, Data science experts can explore a diverse range of career opportunities in several industries.
3. Data science also requires academic credentials- at least a master’s degree. It opens opportunities in the field of research.  
4. Even if you decide not to take up a career as a data scientist, you’d still have a wide variety of career options. For example, a lecturer or a researcher, etc. 
5. Data scientist get chances to travel the world to attend conferences and meetings. 
6. Data scientists get many incentives and perks as part of their job. 
7. Many such jobs are located in developed countries so getting a job like that, especially in a city like Pune would mean that you would have an increased salary and a higher standard of living.

Data science job includes a mix of both technical and business skills. Here are a few business skills you need to become a successful data scientist:

• As a data scientist, you will have to deal with problems. To solve a problem, you must first understand and analyse the issue. Data scientists need to have some great analytical skills and problem-solving abilities.
• Data scientists must have the communication skills to attract clients and market the technology.
•  If you don’t have the curiosity to find answers, you won’t be able to excel as a data scientist. Data science professionals should be curious and passionate about their job
• Data scientist have to be aware of the present trends and client preferences of the industry. So, industry knowledge is essential if you want to become a data scientist. 

Data science though very satisfying is one of the toughest jobs in the world. One has to be well-versed in the technical concepts of data science, master several coding languages and programming platforms and be a great mathematician. Below are the best ways to brush up your data science skills for data scientist jobs:

• If you want to brush up on your Python skills, boot camps are the place to go. Attend boot camps for a crash course on the core concepts of data science 
• Sign up for MOOC courses online to get lectures from industry professionals via video conferencing and live-stream classes. 
• Opt for courses which offer certificates. It adds substantial value to your CV and increases your chances of getting hired
• Try to take up as many projects and assignments as possible for some hands-on experience. 
• Lastly, competitions like Kaggle etc. help you hone your skills by challenging you in new ways

Data science is the field which deals with collecting and analyzing this collected data to predict customer trends and formulate marketing strategies.  Pune is a hub for data science freshers and professionals looking for a job. Here you find several openings in IT, banking, hospitality, and the medical sector. Infosys,  Michael Page, Tata consultancy services, PureEco Tech Solution, Medline Industries, Wolters Kluwer, SG Analytics, etc. are some of the most eminent organizations looking for skilled data scientists.

Data science combines both theory and technical concepts. It involves all kinds of problems and can be applied to all kinds of situations. Data science has ventured into pretty much every sector and is hence extremely important. Here, we have categorized different problems according to their difficulty level and your expertise level:

• Beginner Level
  • Iris Data Set: It is applied in the field of pattern recognition and is the simplest of the lot, best suited for beginners. This dataset has just 4 rows and 50 columns. Practice Problem: The problem is using these parameters to predict the class of the flowers. 
  • Loan Prediction Data Set: The Loan Prediction data set gives the learner experience of working with banking and insurance, and related concepts. It also gives an insight into the kind of challenges in the industry and strategies that can be implemented to deal with it.  This data set has 13 columns and 615 rows and is a classification problem set.Practice Problem: Find out if the loan given will be approved by a bank or not.
  • Bigmart Sales Data Set: This data set is created for retail, and is a great tool for gathering market insights, and plan advertising campaigns. The Bigmart Sales Data Set is especially used for Regression problems and has 12 variables and 8523 rows.Practice Problem: Find out how many sales a retail store can make.
• Intermediate Level:
  • Black Friday Data Set:  The Black Friday Data Set deals with sales transactions that were recorded at a retail store. This data set combines engineering skills with the data of the shopping experience of shoppers during Black Friday. The Black Friday data set comprises of 12 columns and 550,069 rows and deals with a regression problem.Practice Problem: Predict the total purchase made.
  • Human Activity Recognition Data Set: The Human Activity Data Set does exactly what the name says. It deals with data from 30 human subjects that are connected using smartphones with internal sensors. It consists of 561 columns and 10,299 rows.Practice Problem: Predict human activity categorically.
  • Text Mining Data Set: After the Siam Text Mining Competition of 2007, the Text Mining Data Set was obtained. This data set deals with reports related to aviation safety mostly dealing with problems faced by certain flights. The Text Mining Data Set has 30,438 rows and 21,519 columns and is an example of a high dimensional and multi-classification problem.Practice Problem: Classify the documents based on how they’re labelled. 
• Advanced Level:
  • Urban Sound Classification: Consisting of 10 classes with 8,732 sound clippings of urban sounds, this problem introduces the developer to the audio processing in the real-world scenarios of classification. \
    Practice Problem: The problem is the classification of the sound obtained from specific audio. 
  • Identify the digits data set: This data set comprises of 7000 images with a 28x28 dimension ratio and it takes up 31MB of space. These can then be studied and analysed. A developer can even study the elements in each image.
    Practice Problem: Identify the digits present in a given image
  • Vox Celebrity Data Set: Audio Processing is the concept of Deep Learning that is recently becoming popular. The Vox Celebrity Data Set is used for large scale speaker identification. Words spoken by celebrities are extracted from YouTube videos and the data set uses these to aid in isolation and identification of speech recognition. The data set has a collection of 100,000 words spoken by 1,251 celebrities worldwide
    Practice Problem: Identify the celebrity using the given voice sample.

Data science is a lucrative career choice for anyone who is in the IT sector or is enthusiastic about technology. However, the field is not all roses and rainbows. Only those who are passionate about data and want to learn can manage a successful career in this field.  

1. Programming language: Pick a program design language, we prefer R and Python as they’re the easiest of the lot. 
2. Algebra and statistics: Next, master the fundamental concepts of stats and algebra. Data science deals with data (be it textual, numerical, or an image), analysis of this data and creating patterns based on the relationships within them. For this, a basic understanding of algebra and statistics is important. 
3. Data visualization: Data visualization is another area one has to understand and learn how to apply as it makes the content clear and understandable for clients. 
4. Machine Learning: Machine Learning aids developers and data scientists in gathering valuable insights and in-depth analysis. 

Becoming a data scientist is no piece of cake, one really has to burn the midnight oil and gain extensive knowledge on a variety of topics to be well-versed in the field. Here are some of the steps one can take to become a successful data scientist. We have also talked about some core skills required to help you kickstart your career as a data scientist:

• First of all, the candidate needs the appropriate academic degree to be eligible to apply for the data science position in a firm. 
• A degree prepares you for the job and also opens an opportunity for further studies and scope for research. A Ph.D. is an added advantage to the CV.  
• Once you have procured the necessary academic credentials, the next step is to gain adequate industry experience. Participate in contests, complete projects, and assignments, an intern for companies, etc. 
• Learn to work with unstructured data. Your job is to understand the data and manipulate it properly. 
• Sharpen your coding skills, to learn about customizing raw data and how to optimize it.
• Master the popular programming languages, especially platforms like R and Python. 
• After data has properly been collected and sorted, it needs to be analysed using proper algorithms. Deep learning is used to train the model to deal with the data given. 
• Also, practice the basic concepts of data visualization, especially platforms like ggplot. 

Getting a degree in Data Science is important for candidates who want to build a career in this sector. Pune has some of the best IT colleges and educational institutes where you can apply for data science courses. A degree in data science helps data science candidates in the following:

• Expanding their network, meeting experts and getting in touch with professionals in the field.
• Getting a better opportunity in the workspace. The degree course prepares the candidate to face the professional challenges of real-time work.
• Getting better internship offers at corporate firms for work experience and some extra pocket cash 
• Enhancing their credibility as a professional on their CV 

Data science as a field is perhaps one of the most academically acclaimed of all IT ventures. Established organizations and companies hire only data scientists who have at least a postgraduate degree in the subject. 

So, yes, a master’s degree is the most rudimentary requirement for applicants who want to apply for data science. Data science aspirants can look for the best educational institutions and colleges to study data science. Read about the coursework and the curriculum to get a better idea of the kind of topics covered. A post-grad degree also helps candidates apply for higher endeavors in the research sector and work for their PhDs. If you are still confused whether you should go for a Master’s degree, you can try grading yourself on the basis of the below scorecard. If your score is more than 6 points, you should get a Master’s degree:

• A strong STEM (Science/Technology/Engineering/Management) background: 0 point
• A weak STEM background (biochemistry/biology/economics or another similar degree/diploma): 2 points
• A non-STEM background: 5 points
• Less than 1 year of experience in Python: 3 points
• No experience of a job that requires regular coding: 3 points
• Independent learning is not your cup of tea: 4 points
• Cannot understand that this scorecard is a regression algorithm: 1 point

Learning how to code is the most essential skill for anyone in the IT field, regardless of the sector or company one works for. So, yes, of course, it is important that data science candidates learn about the basics of programming languages like Python and R programming. Most of the prominent data science platform is written on some coding platform.

• Most data sets are customized or edited using the code. Data scientists are therefore expected to know coding and programming to learn how to evaluate and establish data sets. 
• Data science involves working with complex statistical figures which cannot be manually calculated. Programming helps data scientists integrate and to implement statistics better.
• Coding skills allow developers to create and optimize a framework, analyze data sets and integrate the data visualization process. 

The average annual remuneration of a Data Scientist in Pune is Rs. 5,89,581.

The average annual salary of a data scientist working in Pune is Rs. 5,89,581. Chennai, on the other hand, has an average annual salary of Rs. 8,19,815 for a Data Scientist.

The average salary of a Data Scientist in Pune is Rs. 5,89,581 as compared to Rs. 6,13,889 in Hyderabad.

A Data Scientist earns Rs. 5,89,581 on an average per year in Pune as compared to Rs. 6,72,492 earned by Data Scientists in Mumbai.

A Data Scientist earns Rs. 5,89,581 on an average per year in Pune as compared to Rs. 6,72,492 earned by Data Scientists in Mumbai.

Needless to say, the demand for Data Scientist in Pune is high. The number of trained data scientists is very less considering the demand for these professionals. The need for a data scientist is high and with the amount of data that needs to be processed, it is clear that this need is only going to rise in the future.

There are a number of benefits of being a Data Scientist in Pune. Being one of the hottest jobs right now, a data scientist gets paid really well. Also, there is an opportunity for tremendous job growth in this field. Data Science is still an unexplored world and as companies realise its potential there will be a hiring spree of data scientists. 

Apart from the handsome payoff, there are several perks and advantages of being a Data Scientist in Pune. The city is affordable and offers multiple job opportunities in the field of Data Science. Data Scientists do not have to work for a particular business or sector. Instead, they can work in any field of their interest including technology, pharma, security and so on. There are so many companies entering the field of Data Science to seek useful business insights that make it a popular field in the city. Also, the city holds meetups, conferences, certification courses, etc. on Data Science that will help you network and excel in the field of Data Science.

The top companies hiring Data Scientists in Pune are Merkle Sokrati, Bloomberg, Cytel Inc, Alpha Predictions LLP, Forgeahead, SG Analytics, Think bumble bee analytics, Eaton, Sleepiz, 3SC Solutions, and many more.

1. Industrial IoT Congress, Pune

• About the conference: IoT Congress is an event based on the innovations that IoT technology is bringing to the industrial ecosystem and enterprises.
• Event Date: 29th Apr, 2019
• Venue: Hotel Novotel Pune Nagar Road, Weikfield IT City Infopark Survey No 30/3, Viman Nagar Road ,Ramwadi, Sakore Nagar, Viman Nagar, Pune, Maharashtra 411014 India
• Days of Program: One 
• Timings: 9:00 AM - 5:00 AM
• Purpose: The primary goal is to establish a concrete data science community and engage in trending topics. 
• Whom can you Network with in this Conference: Industry experts and thought leaders 
• Registration cost: Delegate Registration INR 15000
• Who are the major sponsors: Entraine Business Services UK

2. Data Lake 2019 - Pune

• About the conference: The conference will discuss data lake-a data management architecture that allows organizations to store and analyze a wide variety of structured and unstructured data. 
• Event Date: 15th May, 2019
• Venue: Royal Orchid Central, Kalyani Nagar, Pune, India
• Days of Program: One
• Timings: 8:45AM - 4:30 PM (IST)
• Purpose: Hear important lectures from leading subject experts which includes the latest state-of-the-art, practical applications, research and case studies.
• Whom can you Network in this Conference: Database Administrators, Big Data Professionals, Business Intelligence officials, Database Developers and many other industry professionals.
• Registration cost: INR 10000
• Who are the major sponsors: UNICOM Learning

3. Distributed Systems Conference, Pune

• About the conference: Distributed Systems Conference Conference brings to you a full day of discussion on software architect's responsibilities, including leadership and business skills. 
• Event Date: 16 February, 2019
• Venue: Novotel Pune Nagar Road, Weikfield IT City Infopark Survey No 30/3 Ramwadi, Sakore Nagar, Viman Nagar, Pune, Maharashtra 411014
• Days of Program: One
• Timings: 9:00 AM - 4:30 PM
• Purpose: The program covers software architect's responsibilities, leadership and business skills, by taking on domain-driven design and product management as their basis. 
• Number of speakers: Five
• Speaker's profile: 
• Dr. Sriram Srinivasan, Professor, Cambridge University 
• Dr. Sriram Srinivasan, Trainer and Consultant for Big Data, Hadoop and Apache Apex
• Tushar Gosavi, stream processing using Apache Apex, etc.
• Whom can you Network with in this Conference: Distributed system managers, Evolutionary architecture and thought leaders from all over the world. 
• Registration cost: TBD 
• Who are the major sponsors: Oogway Consulting, Loom, Dheeti, etc. 

4. Matlab Expo, Pune

• About the conference: The conference aims to deliver a lecture on the latest trends in Model-Based Design, technical computing, and signal processing from leading-edge companies, MathWorks experts and using MATLAB and Simulink.
• Event Date: 2nd May, 2019
• Venue: JW Marriott Hotel, Senapati Bapat Road, Pune, Maharashtra 411053
• Days of Program: One
• Timings: 8:30 AM - 5:15 PM
• Purpose: Deep discussions on Data Science and Predictive Analytics, Systems Modeling, Implementation, Verification, Deep Learning and Autonomous Systems.
• Number of speakers: Three
• Speaker's profile: 

• • Mike Agostini, MathWorks 
  • Vinay Jammu, GE Global Research 
• Prashant Rao, MathWorks
• Whom can you Network with in this Conference: Engage with MathWorks technical engineers, MATLAB and Simulink users, and other experts.
• Registration cost: Free Entry 
• Who are the major sponsors: MicroChip, LDRA, OPAL- RT, Speedgoat, etc.

5. IRAJ-International Conference on Big Data, IoT, Cyber Security and Information Technology (ICBDICSIT), Pune

• About the conference: The International Conference will focus on the IoT, Big Data, Cyber Security, and Information Technology (ICBDICSIT) . The conference will provide a premiere platform to discuss and present all the latest researches related to Cyber Security, Big Data and IoT.
• Event Date: 12th May, 2019
• Venue: Kapila business hotel, 174, Dhole Patil Road, Pune, Maharashtra-411001
• Days of Program: One
• Timings: 9:30 AM - 5:00 PM
• Purpose: Exchange new ideas and application experiences face to face, to establish business or research relations and to find global partners for future collaboration.
• Number of speakers: Two 
• Speaker's profile: TBA
• Whom can you Network with in this Conference: CEOs, CTOs and Big Data scientists from all over the country. 
• Registration cost: 
• Academician/Practitioner/Industrialists - INR 6500 
• Student (Masters) - INR 5000
• Student Graduate - INR 4000
• Who are the major sponsors: Crossref, ISSUU, ResearchGate, Scribd., etc.

6. International Conference on Artificial Intelligence, Machine Learning and Big Data Engineering (ICAIMLBDE), Pune

• About the conference: ICAIMLBDE will have a discussion on the latest developments and research outcomes of Machine Learning, Artificial Intelligence, and Big Data Engineering topics.
• Event Date: 19th May, 2019
• Venue: Kapila Business Hotel, 174, Dhole Patil Road, Pune, Maharashtra-411001
• Days of Program: One
• Timings: TBD
• Purpose: The aim of the conference is to make significant offering to the scientific fields. The committee invites authors to present their manuscripts.
• Number of speakers: TBD
• Speaker's profile: TBD
• Whom can you Network with in this Conference: Professors, career professionals, machine learners, big data engineers and artificial intelligence experts. 
• Registration cost: Listeners - INR 3000, Authors - INR 9200, Students - INR 7200
• Who are the major sponsors: IRAJ Research Forum, BASE, Slideshare, Scholarsteer, etc. 
  
  

7. The ASAR- International conference on Machine Learning, Big Data Management and Cloud Computing (ICMBDC), Pune, India

• About the conference: The ICMBDC conference offers an insight into the new techniques and horizons that will contribute to Machine learning Big data management Cloud and Computing in the next few years. 
• Event Date: 19th May, 2019
• Venue: Kapila Business Hotel, 174, Dhole Patil Road, Pune, Maharashtra-411001
• Days of Program: One
• Timings: 9:30 AM - 5:00 PM
• Purpose: All submitted papers will be under peer review and accepted papers will be published in the conference proceedings.
• Number of speakers: Three
• Speaker's profile: 
  • Dr. P. Suresh , M.E, Ph.D. KCE ,Coimbatore, India 
  • Dr. Bommanna Kanagaraj, PSNA College of Engineering and Technology, India 
  • Dr. Yuchou Chang University of Wisconsin, United States.
• Whom can you Network with in this Conference: Academics, industrialists, and career professionals who are dealing with future developments and state-of-art research.
• Registration cost:
  • Academician/Practitioner - INR 7000
  • Student (Masters) - INR 6000
  • Student (Graduate) - INR 5000
  • Listeners - INR 1500
• Who are the major sponsors: Cross ref, DRJI, GIGA Informationszentrum, Springer, etc.

8. International Conference on Big Data, IoT, Cyber Security and Information Technology (ICBDICSIT), Pune, India

• About the conference: ICBDICSIT provides the best platform to discuss and present all the development and research of scientists related to Information Technology, Big Data, Cyber Security and IoT.
• Event Date: June 19th, 2019
• Venue: Kapila business hotel, 174, Dhole Patil Road, Pune, Maharashtra-411001
• Days of Program: One
• Timings: TBA
• Purpose: Present the latest advances of IoT, Big Data, Information Technology, Cyber Security. 
• Number of speakers: TBD
• Speaker's profile: TBD
• Whom can you Network with in this Conference: The conference gives you the chance to network with delegates and global partners and exchange fresh ideas.
• Registration cost: 
• Academician/Practitioner/Industrialists - INR 6500
• Student (Masters) - INR 5000
• Students (Graduate) - INR 4000
• Who are the major sponsors: Slideshare, OAJI, ISSUU, Crossref, etc. 

9. International Conference on Computational Science and Applications (ICCSA) Pune, India 

• About the conference: ICCSA 2019 welcomes the contribution and participation of researchers, professionals, academicians, scientists, and students to present their expertise and knowledge in their fields.
• Event Date: 7th - 9th August 2019
• Venue: MIT-World peace University, S.No.124, Paud Road, Kothrud, Pune, Maharashtra 411038
• Days of Program: Three
• Timings: TBA
• Purpose: The conference focuses on Machine Vision, Data Analytics for Artificial Intelligence, Internet of Things Ambient Intelligence
• Number of speakers: Two 
• Speaker's profile: 
• Ir. Dr Peter Kwan, Data Center Engineer 
• Subhash Bhalla, Professor, IEEE & SIGMOD, ACM.
• Whom can you Network with in this Conference: Innovators, thought leaders and legacy honours from all over the country. 
• Registration cost: 
• Academician - INR 6000
• Students UG / PG - INR 4000
• Foreign Author - $300
• Participants - INR 2000
• Who are the major sponsors: MIT-WPU, Springer, etc.

10. International Conference On Signal Processing And Big Data Analysis (ICSPBA-19), Pune, 2019

• About the conference: ICSPBA-19 is being organised by Science Society-Japan. It provides an opportunity to delegates, research scholars, and students to interact and share their experience and knowledge with their peers.
• Event Date: 18th June, 2019
• Venue: Ginger Hotel, Kala Khadak, Near Indira College, Wakad Naka, Wakad, Pune, Maharashtra 411057
• Days of Program: One
• Timings: TBA
• Purpose: (ICSPBA-19) provides an excellent international platform for sharing knowledge and discussing progress and development in the given fields.
• Number of speakers: TBA
• Speaker's profile: TBA
• Whom can you Network with in this Conference: Practitioners and Researchers from both the industry and academia.
• Registration cost:    
• Student (B.Tech/B.E) - INR 5500 
• Student(M-Tech) - INR 6500 
• PhD/Research Scholar - INR 6500 
• Academian - INR 7500 
• Listeners - INR 2500

1. Pune Data Conference, Pune, India

• Conference City: Pune, India
• About: The Pune Data Conference pooled together the Big Data Analytics community of the city of Pune for a day of various sessions with leading machine learners, Artificial Intelligence, loT, tech leadership and many more. 
• Event Date: 31st, March
• Venue: 36/3-B, Koregaon Park Annexe, Mundhwa Road, Ghorpadi, Pune, 411001, Maharashtra
• Days of Program: One
• Timing: 8:00 AM - 6:00 PM
• Purpose: The purpose of the conference was to create a meaningful conversation between the experienced and the participants on data science and analytics. Pune Data Conference brought together more than 450 delegates from 100 companies and had three parallel sessions. 
• Speakers & Profile:    
  • Robert Sanders, Clairvoyant LLC 
  • Pradeep Mishra, Lymbyc 
  • Vinod Ganesan, Cloudera
• Registration cost: INR 2500 (may vary)
• Who were the major sponsors:    
  • CLAIRVOYANT
  • Globant
  • PARKAR
  • AmDocs 

2. First Annual Pune Data Conference, Pune, India

• Conference City: Pune 
• About: Pune Data Conference focused on discussions and sessions of Hadoop, Data Science and its related ecosystem. 
• Event Date: 15th Apr, 2017 
• Venue: ICC Trade Tower, Senapati Bapat Road, Shivajinagar, Model Colony, Pune, Maharashtra, India
• Days of Program: One
• Timings: 10:00 AM to 06:00 PM IST
• Purpose: Extensive discussion surrounding the Big Data Security, IOT and predictive analytics, along with significant takeaways and action points. 
• Registration cost: INR 2500 (may vary)
• Who were the major sponsors: 
  • Clairvoyant India Pvt Ltd

The ideal path one must follow to secure a job as a data scientist includes the step-wise mastery of skills:

• Getting started
• Mathematics
• Data visualization
• Data preprocessing
• Machine Learning and Deep Learning
• Natural Language processing
• Polishing skills

1. Getting started: Choose a programming language that you are comfortable with. R and Python are both open-source programming languages with a large community and are most preferred in data science. 
2. Mathematics: A data scientist spends a lot of time trying to find patterns in given raw data to make more sense of it. That is why it's important to have a firm grip on both mathematics and statistics. Below are some topics you should focus on: 
• Descriptive statistics
• Probability
• Linear algebra
• Inferential statistics
3. Libraries: From preprocessing the data given to plotting the structured data and finally to applying ML algorithms, there are various processes involved in Data Science. For this, several libraries can be used, such as :
• Scikit-learn
• SciPy
• NumPy
• Pandas
• Ggplot2
• Matplotlib
4. Data visualization: It is a part of your job to make data easier to understand by finding patterns. This can be done by visualizing the data using a graph. The libraries used for this task are:
• Matplotlib - Python
• Ggplot2 - R
5. Data preprocessing: Due to the use of unstructured data, it becomes crucial that data scientists preprocess this data in order to prepare it to be analyzed. Preprocessing is done using feature engineering and variable selection.
6. ML and Deep learning: Deep learning algorithms are used while dealing with a huge set of data. You need to have a tight grasp on topics like CNN, RNN, Neural networks, etc. 
7. Natural Language processing: Every data scientist should be an  NLP expert since it is used to process text data and also involves its classification. 
8. Polishing skills: Competitions like Kaggle etc. provide some of the best platforms to exhibit your data science skills. You can also explore the field by experimenting and creating your own projects. 

If you want to apply for a data science job in Pune, the following steps will increase your chances of success:

• Study: Brush up and reread everything that you have learnt about data science. The few things you can revise are: 
• • Probability
  • Statistics
  • Statistical models
  • Machine Learning
  • Understanding of neural networks.
• Meetups and conferences: Landing a data science job is also about networking. Meetups and tech conferences are a good way to get acquainted with your possible future colleagues and make your presence felt in the industry.
• Competitions: Take part in different competitions like Kaggle and GitHub where you can brush up your skills in a fun way while creating awareness about your capabilities in the market. 
• Referrals: Having a good recommendation can be very important in a job interview. Thus, it is important to keep your LinkedIn profile updated. 
• Know your employer: This is not directly related to data science jobs but in every kind of job. Knowing the organization that you can potentially be a part of will put you ahead of your competition as it gives you a better perspective for your interview.
• Interview: Once you are confident about your skills, it is time to attend interviews. Take as many interviews as you can and do not lose your confidence. Learn from every experience and review your interview to find out where you had gone wrong or how you can answer the questions that you were not able to answer in the future. 

Finding patterns among structured and unstructured data, and analyzing them for the purpose of business growth will be a significant responsibility of a data scientist. In the era of virtual markets and job offerings, there is a continuous flow of data that is structured and unstructured that can prove to be useful in making business decisions. The extraction of information that is appropriate for the industry will be done by data scientists. 

Basic Roles and Responsibilities of a Data Scientist are:

1. Classifying structured and unstructured data through pattern recognition and creating database.
2. Finding data that is relevant to the business and can be profitable from among the vast number of data.
3. Developing Machine Learning technologies, programs and tools which will make accurate analysis of the data.
4. Statistical analysis of appropriate data for predicting future developments of a company is also expected.

Data Science is the hottest job of 21st century and the number one profession in 2019. Due to the extreme demand for data scientists and the limited number of experts in the field data scientists earn at least 36% higher than predictive analytics professionals. The salary of a data scientist depends on two factors:

• Nature of company
• Startups- high pay
• Public- medium pay
• Government and education sector- lowest pay
• Roles and Responsibilities
• Data Scientist: Rs 7,50,741 per year
• Data Analyst: Rs 4,16,649 per year
• Database Administrator: Rs 419,968 per year

A data scientist has the most unique position in a company. He/She will need to have an aptitude for mathematics, understand computer science and at the same time stay aware of current trends. A data scientist not only analyzes data but finds the relevant ones and directs the future of a company by predicting future outcomes. Thus, there are various roles and responsibilities of a data scientist. The following responsibilities are a part of a data scientist's career graph:

• Business Intelligence Analyst: Anyone in this position is expected to analyze the available data to understand the business and marketing trends of the industry his/her company is a part of.
• Data Mining Engineer: An engineer in data science has the task of analyzing data for the company as well as other third parties. Not only that, engineers are expected to optimize data analysis process by developing algorithms.
• Data Architect: A Data Architect's work is to make the data sources more approachable. He/She works alongside developers, system designers to integrate and protect data while finding ways of centralizing it to make it more accessible.
• Data Scientist: The data scientist works as an interpreter by working with sets of data that correspond with particular business ventures and predicts the efficacy of it by developing hypotheses and comparing similar data.
• Senior Data Scientist: Senior data scientist is expected to work with data in order to predict the future of a company. He/She should create projects and develop systems in the present with an eye towards the future so that the future conditions of a company can be predicted.

Below are the top professional organizations for data scientists – 

• Data Science and Machine Learning Meet
• Data Science & Internet of Things (IoT), Pune
• Data Science and Blockchain Pune
• Pune (Big) Data Conference Group
• Open Data-ism

Surveys suggest that a referral is the best way to get hired. To get referred, you must have a vast network. There are many ways to do that: 

• Data science conference
• Online platform like LinkedIn
• Social gatherings like Meetup 

Being the most popular career choice of 2019, there are various career opportunities for a Data Scientist-

1. Data Scientist
2. Data Architect
3. Data Administrator
4. Data Analyst
5. Business Analyst
6. Marketing Analyst
7. Data/Analytics Manager
8. Business Intelligence Manager

Below are the key points on which every data scientist is evaluated while being considered as a potential employee.

• Educational qualifications: Getting a degree in Data Science, like a Master's degree or a Ph.D., will benefit you a lot in the long run. You can also try getting some certifications.
• Programming: Programming is one of the crucial parts of data science. Having good grasp of R programming and Python is important before you delve into other data science libraries.
• Machine Learning: ML and deep learning is required to find patterns and relationships between data after they had been cleaned for processing. Machine learning is imperative for data science projects. 
• Projects: Companies look for hands-on experience in data scientists. Unless you have practical experiences of the theoretical ideas your education is never complete. Thus, having done a series of projects in data science is a good way to showcase your capabilities. 

• Python is a versatile multi-faceted programming language:
• Python is the most simple and readable programming language that instantly attracts data scientists. It comes with appropriate analytic libraries and tools that are ideal for the kind of work done in data science.
• The diversity of resources available on Python makes it a safe option for data scientists.
• Another advantage of using Python is the availability of a community of developers using the same programming language. Python being the most popular programming language, the number of people working on it is high.

Data Science is a huge field which requires working with a large number of libraries. Finding the right programming language to master is, therefore, important for efficient working with all the libraries-

• R programming: The only challenge of R is its steep learning curve, but it is an important language for various reasons:
• • It has a huge open-source community that provides numerous high quality open-source packages for R.
  • It boasts of smooth handling of matrix operations and has large statistical functions.
  • It has included with it ggplot2 that enables data visualization
• Python: With lesser packages than R, Python is still considered to be popular with data scientists. The reasons for that is-
• • Libraries like pandas, scikit-learn and tensorflow equip Python to provide most library needs for data science purposes.
  • It is very easy to use and operate.
  • It has an open-source community that is considered one of the largest one.
• SQL: Working on relational databases, Structured Query Language has-
• • Readable syntax
  • Efficiency in updating, manipulating and querying data for relational databases.
• Java: One of the oldest programming languages, Java has limited libraries limiting its potential. Nevertheless it has some advantages.
  • Systems coded with Java at the backend makes it easier to integrate data science projects with it making it a compatible option.
  • It is a high performance, general purpose, compiled language.
• Scala: Working on JVM, it is considered rather complicated. But it does have some advantages-
• • Running on JVM, Scala can run on Java as well.
  • Used alongside Apache Spark it enables high performance computing cluster.

The following are the steps to download Python 3 for Windows:

• Download and setup: Go to the download page and setup your python on your windows via GUI installer. While installing, select the checkbox at the bottom asking you to add Python 3.x to PATH, which is your classpath and will allow you to use python’s functionalities from terminal.

Alternatively, you can also install python via Anaconda as well. Check if python is installed by running the following command, you will be shown the version installed:

python --version

• Update and install setuptools and pip: Use below command to install and update 2 of most crucial libraries (3rd party):

python -m pip install -U pip

Note: You can install virtualenv to create isolated python environments and pipenv, which is a python dependency manager.

You can simply install python 3 from their official website through a .dmg package, but we recommend using Homebrew to install python as well as its dependencies. To install python 3 on Mac OS X, just follow the below steps:

• Install xcode: To install brew, you need Apple’s Xcode package, so start with the following command and follow through it: 

$ xcode-select --install

• Install brew: Install Homebrew, a package manager for Apple, using the following command: 

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

• Install python 3: To install the latest version of python, use: 

brew install python

• To confirm its version, use: python --version

You should also install virtualenv, which will help you create isolated places to run different projects and may run even on different python versions.