Online Classroom (Weekend)
Apr 04 - May 17 09:00 AM - 12:00 PM ( EDT )
Online Classroom (Weekend)
Apr 04 - May 09 10:00 AM - 02:00 PM ( EDT )
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 analyzing, 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 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).
The Data Scientist job is in the highest demand nowadays and a Data Scientist is the No. 1 job in New Jersey. The job has enormous openings with base salaries of about $102,116. The job is said to have a healthy trend in the long run. In New Jersey, corporations like Fidelity Investments, Jet.com, Audible, Wiley, Charles River Associates, Source Enterprises, Daugherty Business Solutions, etc. employData Scientists.
The popularity of data science is mainly because :
New Jersey is the home of several institutions that provide Master’s degree in Data Science including New Jersey Institute of Technology, Rowan University, Rutgers University, Saint Peter’s University, Stevens Institute of Technology, Thomas Edison State University, etc.
To become a data scientist, the following skills are a necessity:
A successful data scientist should have the following behavioural traits:
Owing to the earning potential, career opportunities rating, and job openings, Data Science has become the No.1 job in the tech world. Corporations like Bank of America, Morgan Stanley, Dow Jones, Liquidnet, Deloitte, JP Morgan Chase, Citi, BirlaSoft, Novartis, Primesys Technologies, TRANZACT, Goldman Sachs, etc. are hiring data scientists to join their team.
Considering the job of a data scientists has been described as the “Sexiest job of the 21st century”, there are definitely certain benefits associated with it, including:
Following the top business skills you must have to become data scientist:
Following are the ways of polishing your skills for data scientist jobs:
Many organizations have adopted Data Science to apply big data analytics. There are several corporations in New Jersey that are looking for Data Scientists to help them make sense of the data like Fidelity Investments, Jet.com, Audible, Wiley, Charles River Associates, Source Enterprises, Daugherty Business Solutions, Bank of America, Morgan Stanley, Dow Jones, Liquidnet, Deloitte, JP Morgan Chase, Citi, BirlaSoft, Novartis, Primesys Technologies, TRANZACT, Goldman Sachs, etc.
If you want to improve your Data Science skills, the best way to do so is to practice solving problems related to Data Science. Depending on the difficulty level of problem you are comfortable with, you can practice the following data science problems:
Given below are the steps needed to become a top data scientist:
To prepare for a data science career, you need to follow the given steps and incorporate the appropriate skills:
New Jersey has several institutions like New Jersey Institute of Technology, Rowan University, Rutgers University, Saint Peter’s University, Stevens Institute of Technology, Thomas Edison State University, etc. that provide a Master’s degree program in Data Science. The course will help you understand the concepts of Data Science and acquire all the skills required to become a top-notch data scientist.
According to a study revealed, 46% of data scientists have a PhD, with 88% of all data scientists having a Master’s degree. The importance of degree in the field is summarized below:
If you want to study Data Science in New Jersey, there are several institutions that offer a postgraduate program in Data Science. But first, you need to figure out if you need a Data Science degree or not. The given scorecard can help you determine whether you should get a Master’s degree. You should pursue the degree if you get over 6 points in total:
Programming knowledge is a must for any aspiring data scientist because:
The average salary of New Jersey based Data Scientist is $100,450 per annum.
In comparison to New York, the average data scientist salary in New Jersey is $734 more.
In New Jersey, the average annual salary of a Data Scientist is $100,450. On the other hand, in Boston, the average annual salary is $125,310.
In Chicago the average annual salary of a Data Scientist is $110,925. On the other hand, in New Jersey, the average annual salary is $100,450.
There is a high demand for data scientists in New Jersey owing to the several firms looking forward to using Data Science while making important business decisions.
Here are the benefits of being a Data Scientist in New Jersey:
Data Scientists have an important role to play in an organization. That offers them certain perks and advantage over others. Not only do they get an opportunity to connect with top-level executives but they also get an opportunity to work in their preferred field. Today, data science has spread its roots in all the fields allowing data scientists to select a field they are actually interested in.
Some of the companies hiring Data Scientists in New Jersey include Comrise, Hackensack Meridian Health and RCI.
|Central NJ Data Science Meetup||Saturday, May 18, 2019||Monmouth Junction, NJ|
|New Jersey Data Science Meetup||Saturday, May 18, 2019||Parsippany-Troy Hills Library|
1. Central NJ Data Science Meetup, New Jersey
2. New Jersey Data Science Meetup, New Jersey
|NJ Edge Conference||11-12 January, 2018||Whippany, New Jersey|
| CIO Conference||11-12 January, 2018|
NJ Tech Council 96 Albany Street, New Brunswick, NJ 08901
1. NJ Edge Conference, New Jersey
2. CIO Conference, New Jersey
Logically, the following step sequence needs to be followed for getting a Data Scientist job:
The steps given below can help you improve your chances of getting data scientist jobs:
The profession of data scientist involves discovery of patterns and inference of information from huge amounts of data, for meeting goals of a business.
Nowadays, data is being generated at a rapid rate, which has made the data scientist job even more important. The data can be used for discovering ideas and patterns that can potentially help advance businesses. A data scientist has to extract information out of data and make relevant sense out of it for benefitting the business.
Roles and responsibilities of data scientists:
As compared to other professionals in predictive analytics, data scientists have 36% higher base salary. The average salary for a Data Scientist is $102,116 per year in New Jersey.
A data scientist can spot trends and use mathematics and computer science skills. Data scientists have to decipher and analyse big data and make future predictions accordingly.
A data science career path can be explained through the following roles:
Following are the top professional organizations for data scientists in New Jersey:
Apart from referrals, other effective ways of networking with data scientists in New Jersey include:
There are numerous career options in the field of data science, including:
Some key points that employers look for while employing data scientists include:
The field of data science is huge involving numerous libraries and it is important to choose a relevant programming language.
The content was sufficient and the trainer was well-versed in the subject. Not only did he ensure that we understood the logic behind every step, he always used real-life examples to make it easier for us to understand. Moreover, he spent additional time to let us consult him on Data Science-related matters outside the curriculum. He gave us advice and extra study materials to enhance our understanding. Thanks, KnowledgeHut!
Overall, the training session at KnowledgeHut was a great experience. I learnt many things. I especially appreciate the fact that KnowledgeHut offers so many modes of learning and I was able to choose what suited me best. My trainer covered all the topics with live examples. I'm glad that I invested in this training.
KnowldgeHut's training session included everything that had been promised. The trainer was very knowledgeable and the practical sessions covered every topic. World class training from a world class institue.
I am really happy with the trainer because the training session went beyond my expectations. Trainer has got in-depth knowledge and excellent communication skills. This training has actually prepared me for my future projects.
The course material was designed very well. It was one of the best workshops I have ever attended in my career. Knowledgehut is a great place to learn new skills. The certificate I received after my course helped me get a great job offer. The training session was really worth investing.
Trainer really was helpful and completed the syllabus covering each and every concept with examples on time. Knowledgehut staff was friendly and open to all questions.
KnowledgeHut has excellent instructors. The training session gave me a lot of exposure to test my skills and helped me grow in my career. The Trainer was very helpful and completed the syllabus covering each and every concept with examples on time.
The Trainer at KnowledgeHut made sure to address all my doubts clearly. I was really impressed with the training and I was able to learn a lot of new things. I would certainly recommend it to my team.
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
A view at a map of the United States will tell you that New Jersey is one of the smallest states. But did you know that it is the most thickly populated state in the union? A state that was the site of several decisive battles during the American Revolutionary War, New Jersey has come a long way. Today is one of the most progressive, well defined places in terms of high-tech and banking headquarters. A vibrant place, New Jersey is surrounded on the southeast and south by the Atlantic Ocean, it borders on the north and east by New York State, on the west by Pennsylvania, and on the southwest by Delaware. Interestingly, the first organized baseball game was played in Hoboken, NJ in 1846. It has the highest number of horses per square mile than any other state. This amazing city is full of opportunities for those armed with the right credentials. KnowledgeHut helps you with this by offering a range of courses to choose from including-- PRINCE2, PMP, PMI-ACP, CSM, CEH, CSPO, Scrum & Agile, Big Data Analysis, Apache Hadoop, and many more.