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 Science has become a popular career choice in Arlington, Texas. Arlington is known as the center of a web that connects hundreds of federal labs, universities, and corporations in the States. It is also home to many leading companies, such as Life Corp, DolEx Dollar Express, D R Horton, Double B Foods, The Pinnacle, etc. Not just in Arlington, data science has become a boon for many companies around the world. Data Science was also named as the Sexiest job of the 21st century by the Harvard review in 2012. Major companies collect data from users, sell them to the ad companies, and make major profits. How else do you think Amazon knows what to recommend to you when you didn’t even ask for it? The answer is simple, data. Here are some of the reasons that make Data Science the sexiest job of the century:
Living in Arlington has many advantages as it is home to many universities renowned for data science degrees, such as Southern Methodist University, Tarleton State University, Texas A & M University-College Station, Texas Tech University, etc. You can also opt for online courses and learn at your own pace. If you want to become a Data Scientist, you need to be skilled in the following:
Being a successful data scientist involves incorporating the following behavioral traits:
Arlington is home to many leading companies, such as Life Corp, DolEx Dollar Express, D R Horton, Double B Foods, The Pinnacle, etc. Also being the sexiest job of the 21st century, data scientists enjoy certain benefits over other professions. Here are the 5 proven benefits of being a Data Scientist:
It is important to have the following business skills if you want to become a successful data scientist:
If you are looking for a job as a Data Scientist in Arlington, here are the 5 best ways to brush up your data science skills:
There are various leading companies headquartered in and around Arlington, TX, such as Life Corp, DolEx Dollar Express, D R Horton, Double B Foods, The Pinnacle, etc. Some companies collect data to sell to other companies while some collect it for their own benefit. Overall, this data is for improving the customer experience. Both types of companies have to hire a data scientist to do the job.
The best way to improve your data science skills is to keep practicing and working your way through Data Science problems. Here, we have categorized different problems according to their difficulty level and your expertise level:
Here are the steps that you must follow in order to become a top-notch Data Scientist:
A job as a Data Scientist sounds very exciting. But the question is how do you become one? Here are some of the steps and key skills required to help you kickstart your career as a data scientist:
Getting a degree in Data Science is very essential if you want to land a job as a Data Scientist. About 88% of data scientists have a Master's degree while about 46% have a Ph.D. degree. Also, there are many universities in Arlington offering Mater’s degree in Arlington, such as Southern Methodist University, Tarleton State University, Texas A & M University-College Station, Texas Tech University, etc.A degree is very important because of the following –
There are many universities in Arlington offering Mater’s degree in Arlington, such as Southern Methodist University, Tarleton State University, Texas A & M University-College Station, Texas Tech University, etc. If you are having trouble in deciding whether you should go for a Master’s degree, you can try grading yourself on the basis of the below scorecard. If your score is more than 6 points, you should get a Master’s degree:
When it comes to becoming a data scientist, the programming language is the most fundamental and important skill regardless of whether you live in Arlington or New York. Here are the reasons why a programming language is required to become a data scientist:
If you want to get a job in the field of Data Science, you need to follow this path:
The 5 important steps to prepare for the job as a Data Scientist involves:
The main aim of a data scientist is to search the raw data or patterns and inference information from it to meet the needs and goals of the business. This data can be present in the form of structured as well as unstructured data.
In the modern world, tons of data are generated every day. This has made the job of a data scientist all the more important. This data is a gold mine of ideas and patterns that can give the business a tremendous growth. It is the job of a data scientist to extract the relevant information from this vast amount of data and benefit the business.
Data Scientist Roles & Responsibilities:
Being the sexiest job of the 21st century comes with its perks. High demand and less supply of data scientists have spiked their base salaries 36% higher than any other predictive analytics professional. The earning of a data scientist depends on the following things:
A Data Scientist has the skills of a computer scientist, a mathematician, and a trend spotter. The main part of a Data Scientist's job is to mine the huge volume of data to decipher patterns and find relationships. This is then used to make predictions for the future. The whole career path of a Data Scientist can be explained as follows:
Business Intelligence Analyst: It is the responsibility of a business intelligence analyst to figure out the business and keep a check on the latest market trends. This can be done by performing the analysis of the data provided by the organization. One needs to have to clear picture of where the organization stands in the business environment.
Data Mining Engineer: The job of a data mining engineer is to examine the data for the business. They often work as a third party. Apart from examining the data, they are also needed for the creation of algorithms that are required in the further data analysis.
Data Architect: Data Architects work alongside developers, system designers, and users. They create the blueprints that are used for the integration, protection, centralization, and maintenance of the data sources. These blueprints are used by data management systems.
Data Scientist: A Data Scientist has the responsibility of doing the analysis, pursuing a business case, developing hypotheses, understanding the data, and exploring patterns from the provided data. After this, comes the development of systems and algorithms that can find a way to use this data in a productive manner. This further improves the interest of the business.
Senior Data Scientist: A Senior Data Scientist is one who anticipates the future needs of the business and shapes the projects according to that. This includes modifying the data analysis process and systems to suit the needs of the future.
If you want to get hired fast in Arlington, referrals are the way to go. You can create your network with other Data Scientists through the following:
There are several career options for a data scientist in Arlington. These include –
Arlington is home to the University of Texas, a major urban research university and hence employers in Arlington generally prefer data scientists to have mastery over some software and tools. They generally look for:
Here are the 5 most popular programming languages used in the Data Science field:
Here is how you can download and install Python 3 on Windows:
Download and setup: Visit the download page and use the GUI installer to setup Python on your windows. Make sure that while you are installing, you select the checkbox asking to add Python 3.x to PATH. This is your classpath that will allow you the usage of Python's functionalities from the terminal.
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:
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
Situated in a state that is rich in history and myth, of legendary cowboys and buried treasures, Arlington is today a vibrant financial centre that houses national and international conglomerates and world class universities. A sporty city to the core, it is home to the Texas Rangers baseball team and several stadiums that host annual sporting events with much fanfare. There are also a number of amusement parks and nature trails to keep one busy over the weekends. This is a great place to start your career and KnowledgeHut helps you along the way by offering internationally recognized courses such as PRINCE2, PMP, PMI-ACP, CSM, CEH, CSPO, Scrum & Agile, MS courses, Big Data Analysis, Apache Hadoop, SAFe Practitioner, Agile User Stories, CASQ, CMMI-DEV and others. Note: Please note that the actual venue may change according to convenience, and will be communicated after the registration.