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).
Investments in the digital enterprise have been drastically increased over the past few years. It has been estimated that by 2020, the IT field will be monitoring 50 times more data than it is today. An interdisciplinary field, data science deals with processes and systems that are used to extract knowledge from large amounts of data.
Known as the ‘city of innovation’, Irvine has become a big tech hub and home to numerous companies, start-ups and innovative people. Home to several leading companies, Irvine is a great place to kickstart your Data Science career because of the multiple opportunities of growth in the city. Some of the corporations offering jobs to Data Scientists include Amazon Web Services, Ten-X, UST Global, Karma Automotive, BookingPal, Allergan, etc.
Looking for a job in data science at Irvine, CA? Here are five reasons why it’s the best career choice for you:
All these factors teamed up with the need for proper utilization of data will hold the key for achieving the set targets for both companies and individuals.
We have developed from complete randomness to finding patterns, predictions to calculations etc. The enablers of such drastic change, that is, the data scientists keep discovering solutions to the most complex problems, create patterns and filter them to give the best results. The University of California located in Irvine offers a Data Science Certificate, Business Intelligence & Data Warehousing Certificate, Predictive Analytics Certificate Program, and Master of Science in Business Analytics. While curiosity is the major catalyst for a career choice like this, there are many technical skills that one must possess in order to not just get hired, but also to thrive.
What do you think makes a good data scientist? Having the essential technical skills is very important, there are some traits that your employers look for during the hiring process.
The combination of technical skills and these characteristics is what differentiates a great data scientist from a mediocre one.
As the field of data science is becoming more popular, plenty of job opportunities have opened up in this field. Some of the leading companies offering employment to Data Scientists include Capital Group, Alteryx, Inc., BlackBerry, Edwards Lifesciences, Drybar, iHerb.com, KPMG, Synaptics, Prismatik, etc. The benefits of being a data scientist are:
Apart from technical skills, a data scientist has to possess skills that can help in finding solutions for real-industry problems.
Being an all-rounder is an empowering feeling. Here are the five best ways to brush up your skills to become a data scientist:
There is a data boom all around the world today. From travel to education to healthcare- data analysis has become extremely crucial. The ‘city of innovation’, Irvine, is flourishing in the travel and healthcare industries. The companies look for different data scientists for different purposes. In Irvine, all corporations including small-sized companies to bir corporations, everyone is looking for data scientists for providing useful insights and helping in making crucial marketing decisions from data to optimize their business. The companies that are currently employing data scientists include Capital Group, Alteryx, Inc., BlackBerry, Edwards Lifesciences, Drybar, iHerb.com, KPMG, Synaptics, Prismatik, Amazon Web Services, Ten-X, UST Global, Karma Automotive, BookingPal, Allergan, etc.
For any goal that one wants to achieve, practicing and working hard are the most important. Find what motivates you to practice what you’ve learned and learn more. This includes personal projects, competitions, online courses, reading research papers or meeting up with experts. To help you decide what kind of data sets you can work with, here are three levels:
Beginner level: This level has data sets that are easy to work with and don’t require complex techniques. They can be solved using basic algorithms.
Intermediate Level: This level has more challenging data sets. It consists of mid and large data sets which require serious pattern recognition skills.
Advanced Level: After getting a hold on the basics, this level will be perfect for people who understand neural networks, deep learning, recommended systems etc. It allows you to get creative.
Ranked as the hottest job on offer in the coming years and coupled with handsome pay-checks, data science has become a top career choice. What will give you the competitive edge? Find out through these steps:
Step 1: Preparation
You can start preparation even before starting your college. Learn Python, Java, and R and rebuild your knowledge in applied math and statistics.
Step 2: Enrol for suitable courses
Try to get enrolled for courses such as data science, mathematics, information technology, computer science, etc. Continue to learn programming languages, database architecture and SQL/MySQL.
Step 3: Get an entry-level job
Companies are often eager to fill entry-level data science jobs. Look for positions such as Junior Data Analyst or Junior Data Scientist.
Step 4: Get a Master’s Degree and/or a Ph.D.
Data science is a field where career opportunities are higher for those with advanced degrees. So, get enrolled for master’s or Ph.D.
Step 5: Never Stop Learning
Staying relevant is crucial to the evolving field of data science. Continue to network and learn through boot camps and conferences.
Most of the data scientists today either hold a Master’s degree or a PhD. While possessing the required skills is the most important requirement to be a data scientist, the degree has statistically proven to be important in landing a job. The University of California located in Irvine offers a Data Science Certificate, Business Intelligence & Data Warehousing Certificate, Predictive Analytics Certificate Program, and Master of Science in Business Analytics. Having a degree has the following advantages:
Candidates having a Master’s/PhD degree may have advantages because they may be able to do some or all of these below:
The University of California located in Irvine offers a Data Science Certificate, Business Intelligence & Data Warehousing Certificate, Predictive Analytics Certificate Program, and Master of Science in Business Analytics. However, a graduate with field experience need not pursue a Master’s if he is already working. Real experience will always outweigh the Master’s degree.
The demand for data scientists is growing in every industry. To become a data scientist, you require the right tools and skillset to produce better results. Data science deals with humongous amounts of data that these scientists need to work on. This data can be segregated or unsegregated, depending on its type. In a situation like this, the basic requirement would be to understand the language in which data communicates. These languages include Python, R, Java, etc.
Broadly, the learning path to become a data scientist can be divided into the following steps:
Data scientists are earning much more as compared to other jobs, especially in the US. Irvine is known for all its start-ups. The start-ups pay the highest, other companies pay lesser and public institutions pay the least. According to the roles:
The ability to manipulate and understand data is extremely critical in innovation. As a result, we are witnessing data science as a field that focuses on the processes and systems that enable us to extract knowledge and transform them into action. But as a discipline, it is in an infancy stage. All tech companies are driven towards data and hence, this is becoming a career with a lot of diversity. The career path in detail is as follows:
Connections are the best option to network with data scientists in Irvine. This can be done through:
They look for:
Python is a structured and object-oriented programming language that contains several libraries and packages that are useful for the purposes of Data Science. The inherent simplicity and readability of Python as a programming language makes it a language that is preferred by data scientists. Another great thing about Python which makes it the language of choice for data scientists is the broad and diverse range of resources that are available.
R Programming: R is one of the most frequently used programming tools for data science. It allows users to compute huge data sets, get statistical insights, create custom graphics and more.
Python: Python is a very popular, dynamic and versatile data tool for analyzing, arranging and integrating data into complicated data sets and creating advanced algorithms. It is among the easiest programming languages and hence the most sought after platform by most data scientists.
SQL: It is used for editing, customizing and arranging information in relational databases.
Java: Java is an extreamely compatible and comprehensive platform which runs on OOPS framework and hence is easy to customize.
The Python download requires about 25 MB of disk space; keep it on your machine, in case you need to re-install Python. When installed, Python requires about an additional 90 MB of disk space.
The following page will appear in your browser
The file named python-3.7.0.exe should start downloading into your standard download folder. This file is about 30 MB so it might take a while to download fully if you are on a slow internet connection.
The file should appear as:
Move this file to a more permanent location, so that you can install Python.
An Open File - Security Warning pop-up window will appear.
A Python 3.7.0 (32-bit) Setup pop-up window will appear.
Ensure that the Install launcher for all users (recommended) and the Add Python 3.7 to PATH checkboxes at the bottom are checked.
If the Python Installer finds an earlier version of Python installed on your computer, the Install Now message may instead appear as Upgrade Now (and the checkboxes will not appear).
A User Account Control pop-up window will appear, posing the question Do you want to allow the following program to make changes to this computer?
A new Python 3.7.0 (32-bit) Setup pop-up window will appear with a Setup Progress message and a progress bar.
During installation, it will show the various components it is installing and move the progress bar towards completion. Soon, a new Python 3.7.0 (32-bit) Setup pop-up window will appear with a Setup was successfully message.
If you can’t find the Applications directory, simply go to Finder by clicking the Finder icon in the Dock (it’s usually the first icon from the left side of the Dock). From there simply, go to the Go menu and select Applications.
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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
Ever since its development in the 1960?s by the Irvine Company, this city has been consistently rated as among the best in America. With its planned business, residential, and recreational spots, Irvine seems to have come out directly out of an architect?s blue print. While there are several banking and technology companies such as Toshiba, Paragon Software, Samsung, and Ford in the city, its picturesque locations, parks and villas have made it a top spot for tourism and film sets. It?s a major hub for arts and culture and sees an annual influx of artists during the Irvine Global Village Festival. Professionals who wish to thrive in their career would find that they can do well here, with certifications such as PRINCE2, PMP, PMI-ACP, CSM, CEH, CSPO, Scrum & Agile, MS courses and others. Note: Please note that the actual venue may change according to convenience, and will be communicated after the registration.