IBM is the second-largest Predictive Analytics and Machine Learning solutions provider globally (source: The Forrester Wave report, September 2018). A joint partnership with Simplilearn and IBM introduces students to integrated blended learning, making them experts in Artificial Intelligence and Data Science. Our Data Science course in Austin which is offered in collaboration with IBM is ideal to make program learners ready to excel in top Data and AI-related careers.
According to the September 2018, Forrester Wave report, IBM is the world’s second-biggest provider of Predictive Analytics and Machine Learning solutions. Simplilearn, working in partnership with IBM, introduces new students to the idea of integrated blended learning, imparting valuable expertise in Artificial Intelligence and Data Science. The Data Science course in Austin, run in collaboration with IBM, prepares students for rewarding careers in the cutting-edge Artificial Intelligence and Data Science industries.
IBM is headquartered in Armonk, New York, and is a respected premier cognitive solutions and cloud platform company, offering a vast selection of technology and consulting services. The company is a known leader in research and development and invests $6 billion annually in these endeavors. IBM has won five Nobel prizes, five US National Medals of Science, six Turing Awards, nine US National Medals of Technology, and 10 inductions into the US Inventors Hall of Fame.
What benefits will this Data Science course in Austin developed in collaboration with IBM give me?
After you finish the Data Scientist online Master's program, you will be awarded completion certificates from IBM and from Simplilearn for their respective courses. The certificates that you'd acquire with the Data Science courses which are part of this Master's program validate your skill level as a expert professional in Data Science and empahsises that you've completed a structured, globally-accepted Data Science training in
Data Scientist is currently one of the most popular IT-related professions. IBM predicts Data Scientist demand will rise by 28% through 2020. Our Data Science course Austin in collaboration with IBM offers you work-ready learning in vital areas such as data mining, clustering, data visualization, statistics, data wrangling, linear and logistic regression, hypothesis testing, regression models and decision trees. You will also learn about Hadoop, PROC SQL, SAS Macros, Spark, recommendation engine, supervised and unsupervised learning, and many more valuable skills.
The Data Scientist training in Austin, co-developed with IBM, focuses extensively in the field, bringing together online instructor-led classes and casual self-paced learning. A capstone project culminates the project and it further enhances your grasp and mastery of the skils by exposing you a real, in-use product that leverages all the skils, tools and techniques you've learned as part of the bootcamp. These same skills will better equip you in becoming a Data Scientist
This Data Science training in Austin features more than 15 real-life, industry-based projects highlighting different domains. These projects help you master concepts of Data Science and Big Data. Here are a few of the projects:
Description: You’ll go through dedicated mentor classes to generate a high-quality industry project where you solve a real-world problem by leveraging the skills and technologies that you learned throughout the program. The capstone project includes all the key points of data extraction, cleaning, and visualization, and how to build and tune models. You can also choose the domain/industry dataset you want to work on, based on whatever options are available.
After you successfully submit your project, you will earn a capstone certificate, showcasing your expanded learning and skills to potential employers.
Project 1: Products rating prediction for Amazon
Amazon, one of the leading US-based e-commerce companies, usually recommends products to customers that fall in a similar category that jibes with their activity and reviews. Amazon would like to boost this recommendation engine by increasing its capabilities, letting it predict ratings for non-rated products and adding them accordingly to the customer’s recommendations.
Project 2: Improving customer experience for Comcast
Description: Comcast, one of the top US-based global telecommunication companies, wants to improve their customer service experience by spotting problem areas that decrease customer satisfaction, and come up with a plan on how to address these issues. The company is also looking for key recommendations that they can put in place to provide the best customer experience.
Project 3: Attrition Analysis for IBM
Domain: Workforce Analytics
Description: IBM, one of the oldest and most popular US-based IT companies, wants you to pinpoint the factors that affect employee attrition. Based on the parameters identified, the company also would like to build a logistics regression model that forecasts employee churn rate.
Project 4: Predict accurate sales for 45 Walmart stores, taking the impact of promotional markdown events into consideration. Walmart is one of America’s leading retail stores. Determine if macroeconomic factors like the Consumer Price Index, unemployment rate, etc., impact their sales.
Description: Walmart holds several promotional markdown events throughout the year. These markdowns typically precede popular holidays and annual events like the Super Bowl, Labor Day, Thanksgiving, and, naturally, Christmas. The weeks where these holidays occur have a weighing factor five times higher in valuation than regular weeks. The company, however, is facing a challenge due to unanticipated demand, a situation made worse by incorrect demand estimation. This results in occasional stock shortfalls. Macroeconomic factors such as CPI, Unemployment Index, etc. can potentially play an important role in predicting demand. However, the company hasn’t yet managed to leverage these factors. A portion of this project involves creating a model to call out the effects of these promotional markdowns on holiday weeks.
Project 5: Learn how the top healthcare industry leaders make use of Data Science to improve their business.
Description: Predictive analytics is a useful tool in many different aspects of healthcare, like mediating hospital readmissions. But no matter what the industry, predictors are most valuable when they’re actionable. Or, put another way, historical and real-time data alone are useless unless the company makes a move. More importantly, in order to ascertain the value and effectiveness of forecasting a trend and ultimately changing the behavior, you must be able to incorporate both the predictor and the intervention back into the same workflow and system where the trend originally started.
Project 6: Understand how Insurance leaders like AIG, AXA, Berkshire Hathaway, etc., use Data Science by working on an insurance-based real-life project in this data science course in Austin
Description: According to information in the 2013 Insurance Predictive Modeling Survey, predictive analytics has risen sharply in the insurance industry, particularly in the biggest companies. For example, the survey shows a predictive modeling boost across the industry, but there are disparities. In fact, every insurance company that writes more than $1 billion in personal insurance uses predictive modeling, while companies who deal with less than that amount hover in the 69% utilization range.
Project 7: See how large banks like Bank of America, Citigroup, ICICI, HDFC, etc. use Data Science to stay ahead of the competition.
Description: A Portuguese banking institution held a marketing campaign to give prospective customers a good reason to invest in a bank term deposit. The bank used phone calls to conduct their marketing campaigns. However, sometimes the same customer got repeated calls, resulting in duplication of effort. Your job is to analyze all the data gathered from this banking marketing campaign.
Project 8: Learn how stock markets like NASDAQ, NSE, and BSE leverage Data Science and Analytics to derive consumable data from complex data sets in this data science training in Austin.
Domain: Stock Market
Description: You must import data from the following companies, using the Yahoo data reader: Amazon, Apple, Google, Microsoft, x and Yahoo. You will be required activities using fundamental analytics, including daily return analysis, multiple plots on closing price, stock trade volumes and stock correlations.
Project 9: Understand how Data Science is used in the field of engineering by engaging in this case study of MovieLens Dataset Analysis.
Description: The GroupLens Research Project is a research group based at the University of Minnesota’s Department of Computer Science and Engineering. The researchers there are involved in several projects related to collaborative filtering, information filtering, and recommender systems.
Project 10: See how top retail companies like Amazon, Walmart, Target, etc. utilize Data Science to analyze and optimize their product placements and stock inventory.
Description: Companies use Analytics to optimize product shelf placement in their stores or the inventory in their warehouses. With this project, participants learn about the daily cycle of product optimization from the warehouse to the shelves. This gives the company insights into regular occurrences in the retail sector.
The most effective Data Scientists possess a combination of experience, data science knowledge, and the appropriate tools and technologies. It’s a great career choice, perfect for both rookies and seasoned professionals alike. Aspiring individuals with an analytical mindset and related training are the ones that can leverage this Data Science training in Austin to the maximum and bag key job roles like:
If any professional is seeking to enroll and extract maximum impact out of this Simplilearn offered Data Scientist Course in Austin, what they’d need would be:
On becoming a program graduate of our Data Science course in Austin, you'd have acquired an in-demand skills set in the field of data science, which you can then use to compete for today's top roles, including:
Data extends into all areas of our lives, and Data Scientists are, unsurprisingly, the top-ranking professionals in any analytics organization. The Glassdoor employment site ranks the Data Scientist profession second in the 50 Best Jobs for 2021. There’s a shortage of Data Scientists, making them much in demand in today’s job market. Data Scientists will be required to understand current technology problem statements, gather and make sense of the data available, create usable data analytical strategies action (using the right tools), effective techniques/algorithms and subsequently offer actionable insights backed by data. That’s why it’s wise to take a data science course in Austin.
On becoming a learner who competes this Data Science course in Austin, you would have with you an in-demand set of skills in data science, making you more than eligible for some exciting jobs, like:
Kickstart your learning of Python for Data Science with this Data Scientist course and familiarize yourself with programming, tastefully crafted by IBM.
This Data Science with Python course gives you a complete overview of Python’s data analytics tools and techniques. Learning python is a crucial skill for many data science roles, and you can develop it with this Python data science course. With a blended learning approach, you can learn Python for data science along with concepts like data wrangling, mathematical computing, and more. Unlock your career as a data scientist with Simplilearn’s Data Science with Python training.
Ensure career success with this Machine Learning course. Learn this exciting branch of Artificial Intelligence with a program featuring Applied Learning, interactive labs, 4 hands-on projects, and mentoring. With our Machine Learning training, master Machine Learning concepts are required for a Machine learning certification. This Machine Learning online course will provide you with the skills needed to become a successful Machine Learning Engineer today.
This Tableau certification course helps you master Tableau Desktop, a world-wide utilized data visualization, reporting, and business intelligence tool. Advance your career in analytics through our Tableau training and gain job-ready skills. Tableau certification is highly regarded by companies for data-related jobs and our Tableau online course trains you to use the tool effectively for preparing data, creating interactive dashboards, adding different dimensions, and drilling into outliers.
Simplilearn’s Data Science Capstone project will give you an opportunity to implement the skills you learned in the Data Science course. Through dedicated mentoring sessions, you’ll learn how to solve a real-world, industry-aligned Data Science problem, from data processing and model building to reporting your business results and insights. The project is the final step in Data Science training and will help you to show your expertise in Data Science to employers.
Our course is exhaustive and this Data Science certification is proof that you have taken a big leap in mastering the domain.
The knowledge and Data Science skills you've gained working on projects, simulations, case studies will set you ahead of the competition.
Talk about your Data Science certification on LinkedIn, Twitter, Facebook, boost your resume, or frame it - tell your friends and colleagues about it.
This course helped a lot. It made me understand how to prioritize important stuff for you. It allowed me to learn and discuss new things like Data Science, Artificial Intelligence, and machine learning. I would also recommend attending Simplilearn's live classes; they give a lot of contexts and are 10x more helpful.
The trainers are very professional and friendly. They have good knowledge of AI/ML and helped me a lot at the beginning of the course as I was completely new to it. After this course, I learned about the various advancements in the field of AI/ML. I am now recognized as a Subject Matter Expert in AI/ML by my organization.
I had an incredible journey completing my Master's Certificate in Data Science. Friends, faculty members, and community support encouraged me to complete this achievement. I've learned multiple scripting languages and expanded my knowledge in statistics, data management/visualization, and machine learning through IBM and Simplilearn.
The entire content is very organized. I got sufficient practical exposure through the live sessions and projects. The course had more implementation than the theoretical part, which helps understand various concepts better. This helped me in applying Data Science to my current role of a Traffic Engineer.
Simplilearn is a gateway for people who want to enter into the fields of Data Science, AI or Cloud. I found this is to be one of the best online instructor-led portals, and I would definitely recommend it. After the course completion, I was able to change my job role from a Hadoop Developer to a Big Data Engineer with a good salary hike.
The study material provided is perfect. And you get lab access on top of that which is very important when trying to learn big data technologies. I also found the live classes very beneficial. The projects and assignments provided help us learn the concepts better. Thanks to Simplilearn.
In a Data Science course, you will learn about many concepts if you are a beginner or an intermediate. This training program is around six to twelve months, often taken by industry experts to help candidates build a strong foundation in the field. Besides the theoretical material, our Data Science course includes virtual labs, industry projects, interactive quizzes, and practice tests, giving you an enhanced learning experience.
This Data Science course in Austin co-developed with IBM will give you an insight into Data Science tools and methodologies, which is enough to prepare you to excel in your next role as a Data Scientist. You will earn an industry-recognized certificate from IBM and Simplilearn that will attest to your new skills and on-the-job expertise. The program will train you on R and Python, Machine Learning techniques, data reprocessing, regression, clustering, data analytics with SAS, data visualization with Tableau, and an overview of the Hadoop ecosystem.
As a part of this Data Science training in Austin, in collaboration with IBM, you will receive the following:
You can enroll in this Data Science training in Austin on our website and make an online payment using any of the following options:
Once payment is received you will automatically receive a payment receipt and access information via email.
Yes, this data science course is suitable for recent graduates as well as experienced professionals who are willing to start a career in data science. There are no specific eligibility requirements to take this course.
Data science is a broad field that involves dealing with large volumes of data to uncover hidden trends and patterns and extract valuable information that aids in better decision-making. Companies that collect massive amounts of data use various data science tools and techniques to build predictive models. Simplilearn’s Data Science training can help you learn all its concepts from scratch.
A Data Scientist is an individual who gathers, cleans, analyzes, and visualizes large datasets to draw meaningful conclusions and communicate them to business leaders. The data is collected from various sources, processed into a format suitable for analysis, and fed into an analytics system where statistical analysis is performed to gain actionable insights.
Yes, we do offer a money-back guarantee for many of our training programs. Refer to our Refund Policy and submit refund requests via our Help and Support portal.
Professionals with no prior knowledge of the field can easily begin with this Data Science course, as you’ll gain a thorough knowledge of the basic concepts as well.
Learners need to possess an undergraduate degree or a high school diploma. Basic knowledge of statistics and a basic understanding of any programming language is recommended.
This Data Science training will familiarize you with programming languages like Python, R, and Scala and data science tools like Apache Spark, HBase, Sqoop, Hadoop, and Flume.
After completing the payment, you will be notified of your successful enrollment through email. It will give you all the details regarding accessing the Data Science course material. Following the steps, you can go through the video lessons instantly.
Companies are embracing digital transformation, and the growing dependency on data makes a career in data science quite promising. Businesses are accelerating their digital initiatives, and data science skills will remain in high demand soon. Moreover, with the existing skills gap, companies are even ready to pay higher salaries to data scientists. With Simplilearn’s Data Scientist course, you can qualify for this rewarding career.
Data science is a vast field; people cannot gain expertise within six months or a year. Learning data science requires specialized technical skills and knowledge of programming basics and analytics tools to get started. However, this Data Science course explains all the relevant concepts from scratch, making it easy to use your new skills.
Simplilearn’s Data Science course is unique because of the following major features:
Following are the list of courses for which you will get IBM certificates:
The course completion certificate received after completing this Data Science course does not expire.
Upon completion of 80% of LVC hours and 2 projects, you will be eligible to receive the Data Scientist Master’s certificate that will testify to your skills as an expert in Data Science. Please find the individual course criteria given below
|Data Science with Python||
|85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and pass 1 project|
|Deep Learning with Keras and TensorFlow||
Data Science Capstone Project
Attendance of 1 Live Virtual Classroom and successful completion of the capstone project
Contact us using the form on the right of any page on the Simplilearn website, select the Live Chat link, or Request a callback.
All of our highly qualified Data Science trainers are industry experts with years of relevant industry experience. Each of them has gone through a rigorous selection process that includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We also ensure that only those trainers with a high alumni rating remain on our faculty.
Our teaching assistants are a dedicated team of subject matter experts to help you get certified in Data Science on your first attempt. They engage students proactively to ensure the course path is being followed and help you enrich your learning experience, from class onboarding to project mentoring and job assistance. Teaching Assistance is available during business hours.
We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after completion of your Data Science course with us.
Yes, Excel skills are beneficial for Data Scientists, and taking an Excel course can be advantageous. Here's why Excel skills are valuable for Data Scientists and how an Excel course can contribute to their work:
Data Exploration and Analysis: Excel provides a user-friendly interface for initial data exploration and analysis. Data Scientists can use Excel to quickly assess data, perform basic calculations, and gain initial insights. An Excel course helps Data Scientists learn advanced data manipulation techniques, such as using formulas, functions, and pivot tables, to analyze and summarize data effectively.
Data Cleaning and Preprocessing: Data cleaning and preprocessing are crucial steps in data science projects. Excel's data manipulation capabilities, combined with an Excel course, equip Data Scientists with skills to handle missing values, remove duplicates, format data, and perform other data cleaning tasks. These skills are essential for ensuring data quality and preparing data for further analysis.
Data Visualization: Visualizing data is a key aspect of data science, as it helps in communicating insights and findings. Excel offers a range of charting and graphing tools that Data Scientists can utilize to create meaningful visualizations. An Excel course teaches Data Scientists how to create visually appealing charts, customize visuals, and present data effectively.
Quick Prototyping and Analysis: Excel's familiarity and ease of use make it a valuable tool for quick prototyping and analysis. Data Scientists can use Excel to perform exploratory data analysis, conduct preliminary modeling, and test hypotheses. An Excel course provides Data Scientists with efficient techniques, shortcuts, and best practices for faster analysis and prototyping.
Collaboration and Communication: Excel is widely used in organizations, making it a common tool for collaboration and communication. Data Scientists can share Excel files, collaborate on data analysis tasks, and integrate Excel outputs into reports or presentations. An Excel course equips Data Scientists with skills for collaborating on workbooks, tracking changes, and effectively sharing insights with team members and stakeholders.
While specialized tools and programming languages are commonly used in advanced data analysis and modeling, Excel skills are still valuable for various data manipulation, exploration, and visualization tasks. By taking an Excel course, Data Scientists can enhance their Excel skills and leverage them strategically throughout different stages of their data science projects.
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