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).
Atlanta, GA offers a unique opportunity to Data Scientists to accelerate their career. The city has been home to several companies that rely heavily on logistics for optimization and efficiency. Companies like HatchWorks Technologies, TopRight, Quatrro, Six Consulting, Inc., 7Factor Software, Stridely solutions, etc. are actively hiring data scientists. There are still not enough experienced data scientists making it one of the highest paid jobs in the tech world.
Atlanta, Georgia is home to several renowned institutions like Georgia Institute of Technology, Georgia State University that offers Master’s degree in Data Science. There are also other options available like certification courses and bootcamp, that will help you learn at your own pace.
A qualified data scientist is expected to be an expert in the following technical skills -
Below are the top 5 essential behavioral traits of a successful Data Science professional-
A lot of local companies in Atlanta, GA have started using data science to help in improving the efficiency and optimizing their business. Companies like Aderant, Sparity Inc, Neudesic, Nexidia, Innovative architects, BI Brainz, PredictX, Keystone Solutions etc, are currently hiring data scientists. So, needless to say, data scientists will be in demand in Atlanta, GA. Below are some other top advantages of being a Data Scientist -
These are the must-have business skills to become a data scientist:
We live in a world of data. And now slowly, different industries have started to realize the importance and benefits of using data science for optimizing their business. Atlanta, GA is home to many such companies that are hiring data scientists either for their own or to use as a third party solution including TopRight, Stridely solutions, HatchWorks Technologies, Quatrro, Six Consulting, Inc., 7Factor Software, Aderant, Sparity Inc, Neudesic, Nexidia, Innovative architects, BI Brainz, PredictX, Keystone Solutions, etc.
Practicing and working is the best way to master any skills. Similarly, you need to work your way through the data science problem as well. Here are a few ways categorized on the basis of difficulty and expertise level:
The importance of degree in the field is summarized below:
There are many colleges in Atlanta, GA that offer Master’s degree in Data Science like Georgia Institute of Technology and Georgia State University. However, before selecting the college, you need to figure out if you need a master’s degree or not. The most ideal approach to decide if you need a Masters in Data Science is by reviewing yourself on the scorecard underneath. The given scorecard can help you figure that out. You should get the degree if you get over 6 points in total:
Knowledge of programming is the most fundamental and important skills required to become a data scientist. Here is why:
A Data Scientist in Atlanta gets an average remuneration of $88,603 per year.
The annual income of data scientist in Atlanta and New York is $88,603 and $99,716 respectively, with a difference of $11,113.
The data scientists earn an average of $88,603 in Atlanta as compared to $110,925 in Chicago.
The average income of a Data Scientist is $77,379 per year in Jersey, Georgia.
In Georgia, the demand for a Data Scientist is quite high. There are several firms that have just started using Data Science and are looking to build a Data Science team that will help them make better business decisions by analyzing their raw data.
Following are the benefits of being a Data Scientist in Atlanta:High SalaryJob growthMultiple job opportunityChance of being an integral part of the team from the start
Data Scientists have a few perks and advantages over other jobs. More often than not, they get to gain attention of the upper level management due to their involvement in getting business insights after the analysis of raw data. Also, they get to pick their field of work as Data Science has spread its roots in almost every field that exists.
Cox Automotive Inc., Charter Global and Norfolk Southern Corporation are among the companies hiring Data Scientists in Atlanta.
|1.||DATA SCIENCE ATL CONFERENCE 2019 || #DSATLConf19||17 Oct, 2019 to 18 Oct, 2019||The Historic Academy of Medicine at GaTech 875 West Peachtree Street Northwest Atlanta, GA 30309 United States|
|2.||Free Thinkful Webinar | Web Development vs Data Science||May 7, 2019||Thinkful Webinar Online Atlanta, GA United States|
|3.||Chris Hyde: An Introduction to Data Science With Python||May 17, 2019||Microsoft Office - Alpharetta 8000 Avalon Boulevard #Suite 900 Alpharetta, GA 30009 United States|
|4.||Data Science North Carolina Conference 2019 || #DSNCConf19||29 Aug, 2019 to 30 Aug, 2019||28223 United States|
|5.||Data Connectors Atlanta Cybersecurity Conference 2019||September 12, 2019||Atlanta, GA United States|
|6.||Angelbeat Technology Seminar on Cloud/Security/AI/Data||July 15, 2019||Atlanta, GA United States|
|7.||Byte to Beautiful: Using GCP to Create an AI Driven Customer Experience||June 4, 2019||Atlanta, Ga United States|
|8.||PerkinElmer Atlanta Automation and Mass Spectrometry Seminar||June 11, 2019|
PerkinElmer Tech Center 11695 Johns Creek Parkway #150 Johns Creek, GA 30097 United States
1. Data Science Atl Conference 2019 || #DSATLConf19, Atlanta
2. Free Thinkful Webinar | Web Development vs Data Science, Atlanta
3. Chris Hyde: An Introduction to Data Science With Python, Atlanta
4. Data Science North Carolina Conference 2019 || #DSNCConf19, Atlanta
5. Data Connectors Atlanta Cybersecurity Conference 2019, Atlanta
6. Angelbeat Technology Seminar on Cloud/Security/AI/Data, Atlanta
7. Byte to Beautiful: Using GCP to Create an AI Driven Customer Experience, Atlanta
8. PerkinElmer Atlanta Automation and Mass Spectrometry Seminar, Atlanta
|1.||Southern Data Science Conference||7 April, 2017|
Hyatt Regency Atlanta Perimeter, 4000 Summit Blvd NE Atlanta, GA
|2.||MLconf Atlanta: The Machine Learning Conference||15 September, 2017||The Academy of Medicine|
Big Data Technology Workshop and 2017 HPCC Systems Summit Community Day. Atlanta, GA, USA
|October 10-12, 2017||Georgia Tech Global Learning Center 84 Fifth Street N.W. Atlanta, GA 30308-1031|
|4.||DataSciCon: Data Science, Data Analytics, Machine Learning, and Big Data conference||November 29, 2017 to December 1, 2017||Georgia Tech Global Learning Center, 84 5th St NW, Atlanta|
|5.||IIA 2018 Analytics Symposium||10 October, 2018|
|6.||Southern Data Science Conference||13-14 April, 2018||Atlanta Marriott Buckhead Hotel & Conference Center|
1. Southern Data Science Conference, Atlanta
2. MLconf Atlanta: The Machine Learning Conference, Atlanta
3. Big Data Technology Workshop and 2017 HPCC Systems Summit Community Day, Atlanta
4. 7th Global Tech Mining Conference, Atlanta
5. DataSciCon: Data Science, Data Analytics, Machine Learning, and Big Data conference, Atlanta
6. IIA 2018 Analytics Symposium, Atlanta
7. Southern Data Science Conference, Atlanta
Below are the steps to get a data science job-
Follow the below steps to increase your chances of success for the job of Data Scientist-
The responsibility of a data scientist is to analyze the vast amount of structured and unstructured data, look for patterns, and inference information. This is done in order to meet the needs and goals of the business.
Today, tons of data is generated every day and this has increased the importance of a Data Scientist. This is because the generated data is filled with ideas and patterns that can help in the advancement of the business. It is the job of a Data Scientist to study the data, extract the relevant information and make sense of this data so that it can benefit the business.
Data Scientist Roles & Responsibilities:
The average salary for a Data Scientist is $101,323 per year in Atlanta, GA.
The Data Science career path can be explained in the following way:
The best way to obtain a job in Atlanta, GA is through Referrals. Some of the additional ways to network with data scientists are:
We have compiled the key points, which the employers generally look for while hiring data scientists:
Here are the 5 most popular programming language used in the field of Data Science:
If you want to download and install Python 3 on Windows, you need to follow these steps:
Alternatively, you can use Anaconda to install python
If you want to check if Python is installed in the system, you can try using the following command that displays the version of the language installed on the system:
python -m pip install -U pip
To install python 3 on Mac OS X, just follow the below steps:
$ ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
$ brew install python
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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