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).
Data scientists are professionals who analyze and manage huge amounts of data. Data Science has evolved as one of the most promising careers today. In today’s date, skilled data scientists are a requirement for every company and industry. The demand for data scientists is growing every year with a predicted rate of 28% growth in demand by 2020. Data has been used for decision making by many organizations in Boston, MA including Vectra, C.R. Bard, Digitas, BD, Localytics, JOYN BIO, Amazon, Spotify, Beacon Health Options, Trianz, Wayfair, etc.
The reasons for the popularity of Data Science as a career choice are as follows:
Fun: Besides its financial and economic aspects, data science comes with many entertaining aspects. It is perfect for people who are curious about new things for it gives a wide scope of creativity and learning. It’s still unexplored, and the more one dives into it, the more new doors will open for him. The huge impact this technology has gives you the freedom to lead your imagination in any direction. Any area, you name it, and data science has the capacity to revolutionize it in a miraculous way.
The top skills that are needed to become a data scientist include the following:
When it comes to Master’s degree in Data Science, Boston, MA has several colleges that will help you get a degree. These colleges include University of Massachusetts, Boston University, and Harvard University.
Below are the top 5 behavioral traits of a successful Data Scientist -
A Harvard Business Review article labeled “data scientist” as the sexiest job of the 21st century. There are several organizations that use data science for business optimization in Boston, MA including Celect, Vertex Pharmaceuticals, Klaviyo, Homesite Insurance, Altisource, The Boston Consulting Group, etc.Some of its benefits can be summarised as follows:
Below is the list of top business skills needed to become a data scientist:
Below are the best ways to brush up your data science skills for data scientist jobs:
Data science has become an important aspect of all kinds of companies and organizations. In Boston, MA, there are several such organizations that hire data scientists like Boston, MA including Celect, Vertex Pharmaceuticals, Klaviyo, Homesite Insurance, Altisource, The Boston Consulting Group, Vectra, C.R. Bard, Digitas, BD, Localytics, JOYN BIO, Amazon, Spotify, Beacon Health Options, Trianz, Wayfair, etc.
To start working on Data Sets and to practice your Data Science skills, you can take up projects to work on. You can categorize it into the following three levels:
Below are the right steps to becoming a successful data scientist:
Here are a few key steps and skills required that will help you get started in the field of Data Science:
There are several institutions in Boston, MA offering a Master’s in Data Science. These colleges include University of Massachusetts, Boston University, and Harvard University. Having a degree in Data Science is very important if you want to get employed as a Data Scientist in Boston, MA. About 88% of data scientists have a Master's degree while about 46% have a Ph.D. degree.
A degree is very important because of the following –
Grade yourself on the basis of the below scorecard to check if you need a Master’s degree in Data Science or not. If your score is more than 6 points, we recommend a Master’s degree:
Knowledge of programming is perhaps the most important and fundamental skill that an aspiring data scientist must possess. Some of the other reasons why knowledge in programming is required include the following:
The average salary of a Data Scientist in Boston is $125,310 per year.
The data scientists earn an average of $125,310 in Boston as compared to $110,925 in Chicago.
A data scientist earns an average of about $125,310 every year in Chicago as compared to $128,623 earned by a Data Scientist in New York.
In Boston, the average annual salary of a Data Scientist is $125,310. On the other hand, in Washington, the average annual salary is $122,328.
Data Scientists earn an average of about $125,310 in Boston as compared to $106,976 in Worcester.
The average earning of a data scientist, about $125,310 every year, in Boston is higher than given to a data scientist in Worcester, which is $84,992.
Data Scientists earns an average of about $125,310 in Boston as compared to $100,449 in Springfield.
All the major organizations in the world are producing data. There is so much data but few skilled people to make sense of it. Boston is in dire need of data scientists who can bring out actionable business insights from raw numbers.
The benefit of being a Data Scientist in Boston is that it is a rapidly evolving field. If you are working as a Data Scientist in Boston, you will get an opportunity to work on new ideas and techniques. Also, your exploration and enthusiasm will be rewarded through exciting projects.
Data Scientists are in top demand right now. The advantage of being a Data Scientist in a city like Boston is the job growth the city offers. With so many companies looking for data scientists, there are multiple options available. This includes small companies as well as big ones. Also, it is easy for a data scientist to connect with top level management as they are the ones involved in converting raw data into useful business insights. A Data Scientist gets to work with the latest technology in a field of their interest.
The Data Science companies with job openings in Boston are Kensho Technologies, Klaviyo, DataRobot, TVision, Agero, Localytics, SHYFT Analytics, GNS Healthcare, Charles River Analytics, Kevmi, True Fit, nToggle, InsightSquared, RapidMiner, etc.
|1.||The Data Science Conference®||23 May, 2019 to 24 May, 2019|
Hyatt Regency Boston 1 Avenue de Lafayette Boston, MA 02111 United States
|2.||ODSC East 2019 - Open Data Science Conference||30 Apr, 2019 to 3 May, 2019|
Hynes Convention Center 900 Boylston St Boston, MA 02115 United States
|3.||Postgres Vision 2019||24 June, 2019 to 26 June, 2019||Sheraton Boston Hotel 39 Dalton St Boston, MA 02199 United States|
|4.||Accelerate AI Summit, ODSC East 2019||30 Apr, 2019 to 1 May, 2019|
Hynes Convention Center 900 Boylston St Boston, MA 02115 United States
|5.||2 Days Seminar Current regulatory thinking on Data Integrity||9 July, 2019 – 10 July, 2019|
Hilton Garden Inn Boston Logan Airport 100 Boardman Street, Boston Massachusetts, Boston MA 02128, Boston MA 02128
1. The Data Science Conference®, Boston
2. ODSC East 2019 - Open Data Science Conference, Boston
3. Postgres Vision 2019, Boston
4. Accelerate AI Summit, ODSC East 2019, Boston
5. 2 Days Seminar Current regulatory thinking on Data Integrity, Boston
|1.||Data Science Conference, Boston||May 23-24, 2018|
Hyatt Regency Boston, One Avenue de Lafayette, Boston, Massachusetts, USA, 02111
|2.||Data Science Meetup, ODSC East 2018||Wednesday, May 2, 2018||Boston Convention Center, 415 Summer Street · Boston, MA|
|3.||Deep Learning for Robotics Summit, 2018||23 - 24th May, 2018||510 Atlantic Avenue, InterContinental, Boston|
|4.||Deep Learning in Healthcare Summit||25 - 26 May 2017||Renaissance Boston Waterfront Hotel, 606 Congress Street, Boston, Massachusetts, 02210|
1. Data Science Conference, Boston
2. Data Science Meetup, ODSC East 2018, Bosto
3. Deep Learning for Robotics Summit, 2018, Boston
4. Deep Learning in Healthcare Summit, Boston
Here is the logical sequence of steps you should follow to get a job as a Data Scientist.
If you are thinking to apply for a data science job, then follow the below steps to increase your chances of success:
A data scientist is an individual who is responsible for discovering patterns and inferencing information from vast amounts of structured as well as unstructured data, in order to meet the business goals and needs.
In this modern business scenario that is generating tons of data every day, the role of a Data Scientist is becoming all the more important. This is because the data generated is a gold mine of patterns and ideas that could prove to be very helpful in the advancement of a business. It is up to the data scientist to extract the relevant information and make sense of it in order to benefit the business.
Data Scientist Roles & Responsibilities:
The national average salary for a Data Scientist is $125,310/yr in Boston, MA. The salary for a data analyst is $73,800/yr while that of a database administrator is $114,714/yr in Boston, MA.
The career path in the field of Data Science can be explained in the following ways:
Business Intelligence Analyst: A business intelligence analyst develops and provides new business intelligence solutions. They may be tasked with defining, reporting on or otherwise developing new structures for business intelligence in ways that will serve a specific purpose. Report writing can be a significant component of this role. They ensure that the business is always in the best position to utilize its most valuable information in a manner that is conducive to its success.
Data Mining Engineer: A Data Mining Engineer performs the following responsibilities:
Data Architect: The responsibilities of Data Architect is to create database solutions, evaluating requirements, and preparing design reports.
Data Scientist: The chief data officer is a senior executive responsible for the utilization and governance of data across the organization through data management, ensuring data quality and creating data strategy. The various roles include the following:
Senior Data Scientist: The Senior Data Scientist oversees the activities of the junior data scientists and supervises and provides advanced expertise on statistical and mathematical concepts for the broader Data and Analytics department.
Referrals are the most effective way to get hired in Boston, MA. Some of the other ways to network with data scientists are:
There are several career options for a data scientist in Boston, MA–
We have compiled the key points, which the employers generally look for while hiring data scientists:
As data science is a huge field and involves multiple libraries to work together in a smooth way, it is essential that you choose an appropriate programming language.
Follow these steps to successfully install Python 3 on windows:
Download and setup: Go to the download page and set up 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 the 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.
To install python 3 on Mac OS X, just follow the below steps:
You should also install virtualenv, which will help you create isolated places to run different projects and may run even on different python versions.
The trainer was really helpful and completed the syllabus on time and also provided live examples which helped me to remember the concepts. Now, I am in the process of completing the certification. Overall good experience.
Everything was well organized. I would like to refer to some of their courses to my peers as well. The customer support was very interactive. As a small suggestion to the trainer, it will be better if we have discussions in the end like Q&A sessions.
Overall, the training session at KnowledgeHut was a great experience. Learnt many things, it is the best training institution which I believe. My trainer covered all the topics with live examples. Really, the training session was worth spending.
KnowledgeHut is a great platform for beginners as well as the experienced person who wants to get into a data science job. Trainers are well experienced and we get more detailed ideas and the concepts.
My special thanks to the trainer for his dedication, learned many things from him. I would also thank for the support team for their patience. It is well-organised, great work Knowledgehut team!
Knowledgehut is the best training provider which I believe. They have the best trainers in the education industry. Highly knowledgeable trainers have covered all the topics with live examples. Overall the training session was a great experience.
I was totally surprised by the teaching methods followed by Knowledgehut. The trainer gave us tips and tricks throughout the training session. Training session changed my way of life. The best thing is that I missed a few of the topics even then I have thought those topics in the next day such a down to earth person was the trainer.
Trainer really was helpful and completed the syllabus covering each and every concept with examples on time. Knowledgehut also got good customer support to handle people like me.
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