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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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).
With more than half the population of the world using the internet and social media platforms it has become imperative to store, organize and analyze the billions of data that is being generated every single second of every day. This has led to the need for Data Scientists who can simplify and isolate data that can be used for optimizing businesses by understanding the choices made by consumers.
Hyderabad is one of the major cities of India. It has many leading companies such as Microsoft, IBM, Amazon, Franklin Templeton, INVECAS, Thrymr Software, Woodcutter, PayZello,etc. operating in the city. These enterprises are in search for skilled data scientists to add to their workforce.
Other major reasons for Data Science becoming a popular career path are:
Hyderabad is home to many renowned technical universities such as IIIT Hyderabad, Havisha Institute, Indian School of Business, Imarticus Learning, University of Hyderabad, Data Analytics Park, etc.which offer courses in the field of data science. The essential skills needed to become a Data Scientist are as follows:
5 behavioral traits are needed in order to become a successful data scientist.
Living in Hyderabad is highly beneficial for a data scientist as it is home to some of the elite universities such as IIIT Hyderabad, Indian School of Business, Imarticus Learning, University of Hyderabad, Data Analytics Park, etc. and companies like Microsoft, IBM, Amazon, Franklin Templeton, INVECAS, Thrymr Software, Woodcutter, PayZello, etc.
Moreover, when more than half of the world’s population is using something you are an expert in, you will definitely get to enjoy its benefits.
Below are the top business skills required to become a successful data scientist-
While you may become an expert in Data science, it is always preferred that you are up to date with the new developments in data science. For that you need to attend:
Anything that gives insight to customer preferences is data. From your hospital prescription, stock investments, browsing history, or favorite color, everything is data and can be used by companies to make ideal products, improving customer experience. Thus the kind of data scientist job you are offered says a lot about the kind of company you are being hired for.
The best way to master any technique is through practice and to master data science the best approach would be to work through problems while solving data science algorithms. There are few data science problems which can be worked on to increase your skills in data science. They are categorized below according to their difficulty level:
The following points will guide you to become a successful data scientist,
Some of the most successful companies in the world rely on data science for their business growth. Google, Amazon, Facebook have offices in Hyderabad and also have the highest rate of employing data scientists. In such a scenario what should you do to get ahead of your peers? Below, listed, are the skill sets and steps you should take,
As mentioned above, most data scientists are Master’s or PhD degree holders. Around 75% are PhD scholars with some background in computer science, mathematics or social sciences. There are perks of having a quantitative education base-
Networking: Interacting with your peer group will help improve clarity and you will find networking opportunities. Having acquaintance in the industry always gives people an edge.
Structured learning: Having a schedule for your curriculum will not only provide a holistic idea about the discipline, it will help in maintaining a schedule and being more productive than in an unplanned situation.
Internships: Getting hands on experience by doing internships can be very helpful and provide you with an idea about the workload you will be expected to take up.
Appropriate academic degrees and qualification: Along with having a degree from a prestigious university, it is also important that you have hands-on experience. In the United States the most common sector which hires data scientists are manufacturing, FMCG, Utility, Consultancy and so on. In contrast data scientists in India are mostly hired in IT and Tech sector or healthcare and financial industries. Thus it is important to have a clear goal at the earliest about which sector one can work in or one wants to work in, so that he/she can pursue the right degree.
Hyderabad is home to IIIT Hyderabad, Havisha Institute, Indian School of Business, Imarticus Learning, University of Hyderabad, Data Analytics Park, etc. These are some of the best universities in India which offer advanced courses in the field of data science. The necessity of a Master’s degree depends on the following points mentioned below. Score yourself according to the factors mentioned, if you score more than 6 points it is advisable that you get done with a master’s degree.
Programming is at the heart of data science and is an absolute must for anyone to learn in order to become a Data Scientist. The other reasons are as follows:
Data sets: A job of a data scientist revolves around analysis of large number of data sets. Knowledge of programming is required to help you analyze those data sets.
Statistics: The ability to program goes hand in hand with your ability to use statistics. As you start working on programming, a lot of statistical techniques will be identified which in turn will make it easier for you to write codes. Without the knowledge of implementation of statistics in data science, statistics will prove to be useless.
Framework: Having programming ability improves an individual's efficiency and ability to structure the data. It is important that data scientists create frameworks for analyzing data so that visualization, interpretation and data pipeline is constructed which will allow selected individuals to access the data at any time. Making the work space efficient is the ultimate responsibility of a data scientist.
The Data Scientist in Hyderabad will earn an income of about Rs. 6,13,889.
The average salary of a Data Scientist in Hyderabad is Rs. 6,13,889 as compared to Rs. 8,19,815 in Pune.
The average salary of a data scientist in Hyderabad is Rs. 6,13,889 as compared to Rs. 6,15,496 in Bangalore.
The annual earnings of a Data Scientist in Hyderabad is Rs. 6,13,889 as compared to Rs. 8,19,815 in Chennai.
Hyderabad is home to several organizations that have just started to dabble in the field of Data Science. They are still new and are searching for data scientists to help them convert their raw data into useful business insights. This makes the demand for Data scientists in the city quite high.
A Data scientist employed in Hyderabad enjoys several benefits. Hyderabad is home to several large as well as medium and small size organizations that are keen on using the power of data to make important business decisions. A data scientist will also get to meet several like minded individuals here through conferences and meetups, as Hyderabad is a hotspot for such events.
Being a data scientist in Hyderabad offers tremendous perks and advantages. The city is filled with startups and established organizations that are looking for data scientists. The city is also a hotspot for several data science conferences, summits, and meetups that allow data scientists to connect and network. They will even get the opportunity to connect with top-level executives in Hyderabad. Also, there are several training institutes that offer certification courses in the field of data science that will help them excel in their field. It's a great city for any Data Scientist to work in their field of interest and enjoy lucrative positions.
The top companies with openings for Data Scientists in Hyderabad are UnitedHealth group, Chiselon Technologies, Accenture, SoCtronics, Julien
Innovations India Pvt Ltd, ZF, Vitreous Health, IBM, Microsoft, JDA Software, etc.
|1.||International Conference on Internet of Things, Big Data Analytics and Information Technology (ICITBDIT - 2019)||25 May, 2019||Hampshire Plaza Hotel, 679 & 80, Lakdikapul, Hyderabad-500004, India|
|2.||International Conference on Big Data, IoT, Cyber Security and Information Technology (ICBDICSIT)||2 June, 2019||Hampshire Plaza Hotel, 679 & 80, Lakdikapul, Hyderabad-500004, India|
|3.||International Conference on Artificial Intelligence & Cognitive Computing||30-31 Aug, 2019||MLR Institute of Technology, Near Gandimysamma Police Station Road, Dundigal, Quthbullapur, Hyderabad, Telangana 500055|
|4.||Practical Data Science By Industry Experts||18 May, 2019||Metasoft Solutions / msmeCloud Pvt. Ltd. Plot No: 12, 2nd Floor,Silicon Valley, Hi-tech City,Madhapur, Hyderabad, Telangana 500081|
|5.||Alexandria | 2 Day Course in NGS Data Analysis & Crispr||18-19 July, 2019||The Grand Plaza Smouha Hotel, Hyderabad|
|6.||Interactive Data Science Demo||11 May, 2019||Kelly Technologies, Flat no. 212, 2nd floor, Annapurna block, Aditya Enclave, Amerpeet, Kumar basti, Hyderabad, Telangana, 500016|
|7.||Data Science and Machine Learning Demystified||11 May, 2019||International School of Engineering (INSOFE), Vamsiram Builders, Hyderabad, India|
|8.||Data Science Course Free Demo By Kelly Technologies||May 12, 2019||Kelly Technologies, Flat no : 212, 2nd floor, Annapurna Block, Aditya Enclave, Ameerpet, Hyderabad-16.|
|9.||Best Azure Data Analytics Training Institute in Hyderabad-AcuteLearn Technologies||9 May, 2019||Acutelearn Technologies, Vip Hills, Jaihind Enclave, Madhapur, Hyderabad, India|
1. International Conference on Internet of Things, Big Data Analytics and Information Technology (ICITBDIT - 2019), Hyderabad
2. International Conference on Big Data, IoT, Cyber Security and Information Technology (ICBDICSIT), Hyderabad
3. International Conference on Artificial Intelligence & Cognitive Computing, Hyderabad
4. Practical Data Science By Industry Experts, Hyderabad
5. Alexandria | 2 Day Course in NGS Data Analysis & Crispr, Hyderabad
6. Interactive Data Science Demo, Hyderabad
7. Data Science and Machine Learning Demystified, Hyderabad
8. Data Science Course Free Demo By Kelly Technologies, Hyderabad
|1.||Data Science for Real World Conference - 2017||Sunday, 22nd Oct 2017||Hyderabad Marriott Hotel & Convention Centre, Tank Bund Road, Opposite Hussain Sagar Lake, Hyderabad, Telangana, India|
|2.||5th International Conference on Big Data Analytics (BDA 2017)||December 12-15, 2017||IIT Hyderabad, Telangana State, India|
1. Data Science for Real World Conference - 2017, Hyderabad
2. 5th International Conference on Big Data Analytics (BDA 2017), Hyderabad
The ideal path to securing a job as a data scientist is as follows:
Getting started: Learning any programming language is the best way to start your journey as a data scientist. The most common programming languages are the R and Python programming. Having an idea of what data science is and what type of jobs it entails should be the first priority.
Mathematics: Data science is the study of data. It requires raw data to be stored, segregated and finally interpreted, which requires both mathematics and statistics. Having good command over few of the aspects of statistics can be quite helpful in data science, like:
Libraries: Data science is an advanced level of inventory making. Thus it not only preprocesses the data, but plots it as structured data and then uses AI algorithms on it to create databases. Some of the most popular libraries are:
Data Visualization: Having the presence of mind to categorize the raw data, finding similarities and being able to simplify the data for easy understanding is to visualize the data. One of the popular forms is graph. There are various libraries you can use to make it easier for you:
Data preprocessing: Data scientists start with a large mass of data that needs to be preprocessed in order to be analysis ready. The preprocessing is done with feature engineering and variable selection. After this it is fed to ML tools for analysis.
Deep learning and ML: Machine Learning and deep learning are the medium through which data is analyzed. The preprocessed data will work only with deep learning algorithms in order to analyze such huge number of data. Both deep learning and ML are mandatory for your job application to be even considered. One should spend a few weeks reading up on CNN, RNN and neural networks.
Natural Language processing: One should have knowledge of NLP as it helps in analyzing text form of data and classifying them as well.
Polishing skills: There is no end to knowledge and competitions are a great way to brush up on your programming skills. Online platforms like Analytics Vidya or Kaggle have opportunities to keep working on your data science concepts. Outside online platforms you can make your own projects and study it.
If you think you are prepared to take an interview as a Data Scientist, the following ways might help you prepare for the interview.
Study: Reread whatever you have learnt till now. There are few things you could brush up on:
Meetups and Conferences: Going to tech summits or developer meetups will acquaint you with the people who could one day become your colleagues. This is a good way to do networking too.
Competitions: Competitions are the best platforms to test your skills. Taking up projects to work on from Kaggle or GitHub would help polish your skills.
Referral: Having good referrals is considered one of the most important parts of a job interview. You should always keep your LinkedIn profile updated.
Know your Employer: Always do research on the organization you are joining. Having an idea of the type of company and values the company has will give you a new perspective.
Interview: Once you feel that you are ready for taking an interview, take one. Be comfortable and learn from your experience. Think of where you went wrong and how you could have answered the tricky questions differently.
Making data easy to infer from is the job of a data scientist. Finding patterns among structured and unstructured data, and analyzing them for the purpose of business growth will form a significant responsibility of a data scientist. In the era of virtual markets and job offerings there are 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:
Data Science is the hottest job of 21st century and is 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. Moreover, companies like Microsoft, IBM, Amazon, Franklin Templeton, INVECAS, Thrymr Software, Woodcutter, PayZello, etc have a branch in Hyderabad and are looking for skilled data scientists. This makes Hyderabad very valuable for an aspiring data scientist. The average salary for a Data Scientist is ₹ 7,47,063 per year in Hyderabad, Telangana.
A data scientist has the most unique position in a company. He/She will need to have an aptitude for mathematics, understands 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.
The following responsibilities are a part of a data scientists career graph:
There are various ways one can look for possible employees:
Being the most popular career choice of 2019 there are various career opportunities of a Data Scientist-
Elite companies like Microsoft, IBM, Amazon, Franklin Templeton, INVECAS, Thrymr Software, Woodcutter, PayZello, etc have branches in Hyderabad and are in search of data science professionals. Below are the key points on which every data scientist is evaluated for being considered as a potential employee.
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 to work efficiently 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
Python: With lesser packages than R, Python is still considered to be popular with data scientists. The reasons for that is-
SQL: Working on relational databases, Structured Query Language has-
Java: One of the oldest programming languages, Java has limited libraries limiting its potential. Nevertheless it has some advantages.
Scala: Working on JVM, it is considered rather complicated. But it does have some advantages-
The following are the steps to downloading 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 -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:
command and follow through it: $ xcode-select --install
/usr/bin/ruby -e “$(curl -fsS https://raw.githubusercontent.com/Homebrew/install/master/install)”Confirm if it is installed by typing: brew doctor
You should also install virtualenv, which will help you create isolated places to run different projects and may run even on different python versions.
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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