Rapid technological advances in Data Science have been reshaping global businesses and putting performances on overdrive. As yet, companies are able to capture only a fraction of the potential locked in data, and data scientists who are able to reimagine business models by working with Python are in great demand.
Python is one of the most popular programming languages for high level data processing, due to its simple syntax, easy readability, and easy comprehension. Python’s learning curve is low, and due to its many data structures, classes, nested functions and iterators, besides the extensive libraries, this language is the first choice of data scientists for analysing, extracting information and making informed business decisions through big data.
This Data science for Python programming course is an umbrella course covering major Data Science concepts like exploratory data analysis, statistics fundamentals, hypothesis testing, regression classification modeling techniques and machine learning algorithms.Extensive hands-on labs and an interview prep will help you land lucrative jobs.
Get acquainted with various analysis and visualization tools such as Matplotlib and Seaborn
Understand the behavior of data;build significant models using concepts of Statistics Fundamentals
Learn the various Python libraries to manipulate data, like Numpy, Pandas, Scikit-Learn, Statsmodel
Use Python libraries and work on data manipulation, data preparation and data explorations
Use of Python graphics libraries like Matplotlib, Seaborn etc.
ANOVA, Linear Regression using OLS, Logistic Regression using MLE, KNN, Decision Trees
There are no prerequisites to attend this course, but elementary programming knowledge will come in handy.
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Interact with instructors in real-time— listen, learn, question and apply. Our instructors are industry experts and deliver hands-on learning.
Our courseware is always current and updated with the latest tech advancements. Stay globally relevant and empower yourself with the training.
Learn theory backed by practical case studies, exercises and coding practice. Get skills and knowledge that can be effectively applied.
Learn from the best in the field. Our mentors are all experienced professionals in the fields they teach.
Learn concepts from scratch, and advance your learning through step-by-step guidance on tools and techniques.
Get reviews and feedback on your final projects from professional developers.
Get an idea of what data science really is.Get acquainted with various analysis and visualization tools used in data science.
Hands-on: No hands-on
In this module you will learn how to install Python distribution - Anaconda, basic data types, strings & regular expressions, data structures and loops and control statements that are used in Python. You will write user-defined functions in Python and learn about Lambda function and the object oriented way of writing classes & objects. Also learn how to import datasets into Python, how to write output into files from Python, manipulate & analyze data using Pandas library and generate insights from your data. You will learn to use various magnificent libraries in Python like Matplotlib, Seaborn & ggplot for data visualization and also have a hands-on session on a real-life case study.
Visit basics like mean (expected value), median and mode. Understand distribution of data in terms of variance, standard deviation and interquartile range and the basic summaries about data and measures. Learn about simple graphics analysis, the basics of probability with daily life examples along with marginal probability and its importance with respective to data science. Also learn Baye's theorem and conditional probability and the alternate and null hypothesis, Type1 error, Type2 error, power of the test, p-value.
Write python code to formulate Hypothesis and perform Hypothesis Testing on a real production plant scenario
In this module you will learn analysis of Variance and its practical use, Linear Regression with Ordinary Least Square Estimate to predict a continuous variable along with model building, evaluating model parameters, and measuring performance metrics on Test and Validation set. Further it covers enhancing model performance by means of various steps like feature engineering & regularization.
You will be introduced to a real Life Case Study with Linear Regression. You will learn the Dimensionality Reduction Technique with Principal Component Analysis and Factor Analysis. It also covers techniques to find the optimum number of components/factors using screen plot, one-eigenvalue criterion and a real-Life case study with PCA & FA.
Learn Binomial Logistic Regression for Binomial Classification Problems. Covers evaluation of model parameters, model performance using various metrics like sensitivity, specificity, precision, recall, ROC Cuve, AUC, KS-Statistics, Kappa Value. Understand Binomial Logistic Regression with a real life case Study.
Learn about KNN Algorithm for Classification Problem and techniques that are used to find the optimum value for K. Understand KNN through a real life case study. Understand Decision Trees - for both regression & classification problem. Understand Entropy, Information Gain, Standard Deviation reduction, Gini Index, and CHAID. Use a real Life Case Study to understand Decision Tree.
Understand Time Series Data and its components like Level Data, Trend Data and Seasonal Data.
Work on a real- life Case Study with ARIMA.
A mentor guided, real-life group project. You will go about it the same way you would execute a data science project in any business problem.
Project to be selected by candidates.
With attributes describing various aspect of residential homes, you are required to build a regression model to predict the property prices.
This project involves building a classification model.
Predict if a patient is likely to get any chronic kidney disease depending on the health metrics.
Wine comes in various styles. With the ingredient composition known, we can build a model to predict the Wine Quality using Decision Tree (Regression Trees).
Data science job is considered as one of the hottest jobs of the 21st century because of the various benefits it offers. A skilled data scientist is the need of today's competitive market. The job involves developing various methods by which data can be collected so that useful and relevant information can be sorted out. The main motive of data science is to solve analytically complex problems and to obtain insights from any type of data, whether specific or non-specific. Data Science is also often used interchangeably with earlier concepts like business analytics, business intelligence, predictive modeling, and statistics. Mumbai is a great place to be for an aspiring data scientist as it has some of the most recognized companies in the field such as Google, S2 Infotech, BookMyShow, Tata CLiQ, CreditMate, JP Morgan Chase & Co, Truebil etc.
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 -
The top 5 behavioral traits of a successful Data Scientist are -
There are many benefits to being in the job declared as the ‘Sexiest job of the 21st century’ by Harvard Business review in 2012:
Below are the must-have business skills you need to become a data scientist-
Following are the best ways to brush up your data science skills for data scientist jobs:
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:
Here are the right steps that you need to follow to become a top-notch data scientist:
Below are the right steps to becoming a successful 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 –
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:
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, India||10th June - 11th June, 2019||Renaissance Mumbai Convention Centre Hotel, 2 & 3B, Near Chinmayanand Ashram, Powai, Mumbai, Maharashtra 400087|
|2.||The MachineCon, 2019, Mumbai, India||24th May, 2019||Novotal Juhu, Mumbai|
|3.||Data Workshop and Meetup, Pydata initiative, Mumbai, India||May 18, 2019||91springboard Vikhroli, Opposite Vikhroli Bus Depot, Vikhroli West · Mumbai|
|4.||DataGiri's Code-along Saturdays, Mumbai, India||11th May, 2019||TBA|
|5.||Deep Learning with Computer Vision in FinTech, Mumbai, India||May 11, 2019||Rise Mumbai 1902, 19th floor Tower B, Peninsula Business Park Lower Parel, Mumbai|
|6.||Machine Learning - A Graphical Intuition, Mumbai, India||12 May, 2019||CETTM - Center for Excellence in Telecom Training and Management, MTNL Technology Street, Hiranandani Gardens, Powai, Mumbai, Maharashtra 400076|
|7.||IDF Mumbai Online Meetup, Mumbai, India||May 17, 2019||Online|
|8.||The Fifth Elephant Winter 2019, Mumbai, India||Friday, 18th Jan, 2019||ISDI ACE, Colab Area, 7th Floor, Tower 2A, One Indiabulls Center, Lower Parel, Mumbai, Maharashtra - 400013|
|9.||Asian Conference on Recent Advances in Science, Engineering and Technology, Mumbai, India||2 May, 2019||Radisson Mumbai Goregaon, Mumbai, India|
|10.||India IOT SUMMIT 2019, Mumbai, India||8th Feb, 2019||Hotel ITC Maratha, Mumbai|
1. Gartner Data & Analytics Summit 2019, Mumbai
2. The MachineCon, 2019, Mumbai
3. Data Workshop and Meetup, Pydata initiative, Mumbai
4. DataGiri's Code-along Saturdays, Mumbai
5. Deep Learning with Computer Vision in FinTech, Mumbai
6. Machine Learning - A Graphical Intuition, Mumbai
7. IDF Mumbai Online Meetup, Mumbai
8. The Fifth Elephant Winter 2019, Mumbai
9. Asian Conference on Recent Advances in Science, Engineering and Technology, Mumbai
10. India IOT SUMMIT 2019, Mumbai
|1.||Data Science Congress, 2018||29/05/2018 - 1/6/2018||CIDCO Convention Centre, Mumbai|
|2.||Data Visualisation Summit, Mumbai||September 01, 2017||The Lalit, Mumbai, Sahar Airport Road, Andheri East, Mumbai.|
|3.||Gartner Data & Analytics, Summit 2017||6 – 7 June, 2017||Renaissance Mumbai Convention Centre Hotel, #2 & 3B, Near Chinmayanand Ashram, Powai, Mumbai|
|4.||India IoT Summit 2017||August 22-23, 2017||The Lalit, Sahar Airport Rd, Navpada, Marol, Andheri East, Mumbai, Maharashtra|
1. Data Science Congress 2018, Mumbai
2. Data Visualisation Summit, Mumbai
3. Gartner Data & Analytics, Summit 2017, Mumbai
4. India IoT Summit 2017, Mumbai
Below are the steps you should follow to get a job as a Data Scientist.
Here is what you need to prepare for a job as a data scientist:
The major roles and responsibilities of a Data Scientist include the following:
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:
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:
Here are the tools and software that you need to master to be preferred over other data scientists by the employers:
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:
Here is how you can download and install Python 3 on Windows:
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 -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:
/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)" Confirm if it is installed by typing: brew doctor
brew install python
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.
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Python is a rapidly growing high-level programming language which enables clear programs on small and large scales. Its advantage over other programming languages such as R is in its smooth learning curve, easy readability and easy to understand syntax. With the right training Python can be mastered quick enough and in this age where there is a need to extract relevant information from tons of Big Data, learning to use Python for data extraction is a great career choice.
Our course will introduce you to all the fundamentals of Python and on course completion you will know how to use it competently for data research and analysis. Payscale.com puts the median salary for a data scientist with Python skills at close to $100,000; a figure that is sure to grow in leaps and bounds in the next few years as demand for Python experts continues to rise.
By the end of this course, you would have gained knowledge on the use of data science techniques and the Python language to build applications on data statistics. This will help you land jobs as a data analyst.
Tools and Technologies used for this course are
There are no restrictions but participants would benefit if they have basic programming knowledge and familiarity with statistics.
Yes, KnowledgeHut offers virtual training.
On successful completion of the course you will receive a course completion certificate issued by KnowledgeHut.
Your instructors are Python and data science experts who have years of industry experience.
Any registration canceled within 48 hours of the initial registration will be refunded in FULL (please note that all cancellations will incur a 5% deduction in the refunded amount due to transactional costs applicable while refunding) Refunds will be processed within 30 days of receipt of a written request for refund. Kindly go through our Refund Policy for more details.
In an online classroom, students can log in at the scheduled time to a live learning environment which is led by an instructor. You can interact, communicate, view and discuss presentations, and engage with learning resources while working in groups, all in an online setting. Our instructors use an extensive set of collaboration tools and techniques which improves your online training experience.
Minimum Requirements: MAC OS or Windows with 8 GB RAM and i3 processor