As shown in the Forrester Wave report from September 2018, IBM is the second-largest provider of Predictive Analytics and Machine Learning solutions in the world. Simplilearn with this course (offered in collaboration with IBM) trains learners via applied learning offering them a chance to gain unparalleled expertise in AI and Data science. The Data Science course in Muscat gets students ready for a rich career in the fields of Artificial Intelligence and Data Science.
Headquartered in Armonk, New York, IBM is a respected leader in premier cognitive solutions and cloud platforms, offering a vast selection of technology and consulting services. The well-established company is an acknowledged leader in research and development, investing $6 billion annually into these fields. 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 Muscat developed in collaboration with IBM give me?
You will receive certificates from IBM and Simplilearn for their respective courses, once you finish the Data Scientist online Master's program. The certificates that learners earn via our Data Science course in Muscat is proof of their knowledge in the data science realms and is an attestation that they've successfully undergone this Data Science training in Muscat. You will also receive:
The Data Scientist profession is one of the most popular IT-related professions available today. IBM predicts that the need for Data Scientists will increase by 28% in 2020. Our Data Science course in Muscat (delivered as an IBM collaboration) trains you for key skills - data visualizations, clustering, data mining, wrangling, regression models, logistic and regression testing, hypothesis testing, and statistics. The course also explores Hadoop, PROC SQL, SAS Macros, Spark, recommendation engine, supervised and unsupervised learning, and other valuable skills.
The Data Scientist Master’s program focuses on extensive Data Science training, combining online instructor-led classes and relaxed self-paced learning. Our program offering Data Science training in Muscat ends in a Capstone project which is a culmination of all that you've learned by allowing you to work on actual business problem statements, solving which would require the application of everything you've learned in this course. All of these skills will help you become an expert Data Scientist.
This Data Science training in Muscat boasts of more than 15 real-life, industry-based projects, emphasizing different domains. These projects help you grasp the more well-used concepts of Data Science and Big Data. Here are some of the projects you will encounter:
Capstone Project:
Description: Dedicating mentoring will be available as you work on an highly industry-relevant project which has you solving a real, industry problem via the skills and technologies you'd have mastered via our bootcamp. 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
Domain: E-commerce
Amazon, one of the top US-based e-commerce companies, habitually recommends products to customers that fall in categories that mesh with their past product activity and reviews. Amazon intends to enhance its recommendation engine, boost its capabilities - making it capable to make rating predictions on non-related products and having them included on the recommendation list shown to the customer.
Project 2: Improving customer experience for Comcast
Domain: Telecom
Description: Comcast, one of the top US-based global telecommunication companies, wants to take their customer service experience to the next level by locating problem areas that reduce customer satisfaction. Once these areas are found, Comcast wants a plan on how to solve this dilemma. The company is also looking for useful strategies that they can put in place to deliver the best customer experience.
Project 3: Attrition Analysis for IBM
Domain: Workforce Analytics
Description: IBM is one of the United States’ oldest and most well-known IT companies. This computer giant wants you to pinpoint the factors that influence employee attrition. Also, using the parameters identified, the company would like to develop a logistics regression model that predicts the employee churn rate.
Project 4: Predict accurate sales for 45 Walmart stores, taking into consideration the impact of promotional markdown events. Walmart is one of America’s main retail stores. Figure out if macroeconomic factors like the Consumer Price Index, unemployment rate, etc., impact their sales.
Domain: Retail
Description: Walmart typically holds several promotional markdown events during the year. These markdowns usually revolve around popular holidays and annual events such as Labor Day, Thanksgiving, the Super Bowl, and of course, Christmas. The weeks with these holidays have a weighing factor five times higher in valuation than the normal, uneventful weeks. Walmart, however, is facing a challenge because of unanticipated demand, a situation made worse thanks to incorrect demand estimation. This flawed estimation results in the occasional stock shortfall. Macroeconomic factors like CPI, Unemployment Index, etc. can play an important role in predicting demand, but the company hasn’t yet figured out how to leverage these factors. Part of this project involves creating a model to highlight the effects of these promotional markdowns on the holiday weeks.
Project 5: Learn how top healthcare industry leaders use Data Science to improve their business in this data science course in Muscat.
Domain: HealthCare
Description: Predictive analytics is a valuable tool for many facets of healthcare, like mediating hospital readmissions, for example. But regardless of the industry, predictors offer the most value when they can be acted upon. In other words, historical and real-time data alone are useless until the company takes appropriate action. Furthermore, in order to predict the value and effectiveness of forecasting a trend and thereby change its behavior, you have to be able to reintroduce both the predictor and the intervention into the same workflow and system where the trend originally began.
Project 6: Work on an insurance-based real-life project to understand how insurance leaders like AIG, AXA, Berkshire Hathaway, etc., use Data Science.
Domain: Insurance
Description: According to data found in the 2013 Insurance Predictive Modeling Survey, predictive analytics have increased noticeably in the insurance industry, especially among the larger companies. The survey shows a predictive modeling boost across the industry, but the trends are inconsistent. For example, every insurance company writing over $1 billion in personal insurance uses predictive modeling, but companies who deal with less than $1 billion are set 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 their competition.
Domain: Banking
Description: A Portuguese banking institution launched a marketing campaign to give potential customers a compelling reason to invest their money in a bank term deposit. The bank used phone calls for this marketing campaign. Unfortunately, sometimes a customer got multiple calls from the campaign. Your job is to analyze all the relevant data obtained from this marketing campaign.
Project 8: Understand how stock markets like NASDAQ, NSE, and BSE leverage Data Science and Analytics to gather consumable data from complex data sets.
Domain: Stock Market
Description: You will use the Yahoo data reader to import data from the following companies: Amazon, Microsoft, Apple, Google, and Yahoo. You must then use this data to perform fundamental analytics functions such as plotting closing price, plotting stock trade by volume, running daily return analysis, and using pair plots to show the correlations between stocks.
Project 9: Learn how Data Science is used in the field of engineering by working on this case study of MovieLens Dataset Analysis.
Domain: Engineering
Description: The GroupLens Research Project is a research group at the University of Minnesota’s Department of Computer Science and Engineering. The researchers are involved in several projects relating to collaborative filtering, information filtering, and recommender systems.
Project 10: Explore how top retail companies like Amazon, Walmart, Target, etc. utilize Data Science to analyze and optimize their product placements and stock inventory.
Domain: Retail
Description: Big businesses use Analytics to optimize their product shelf placement in stores and their warehouse inventory. This project helps participants learn about the daily cycle of product optimization, taking it from the warehouse to the shelves. This cycle provides the company with insights into regular happenings in the retail sector.
The best Data Scientists have an eclectic mixture of experience, data science knowledge, and the associated tools and technologies. It’s a fantastic career path, suitable for rookies and seasoned experts alike. Individuals having a passion for data science, an analytical mindset and good education will find this Data Science training in Muscat to be most beneficial; these include:
If individuals are looking to enroll and get the best out of this Data Scientist Course in Muscat, they’d need
Kickstart your learning of Python for Data Science with this introductory course and familiarize yourself with programming, tastefully crafted by IBM.
This Data Science with Python certification 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 58 hrs of 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 certification 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 Data Scientist course is exhaustive and this certificate 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.
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. As companies are collecting massive amounts of data, they use various data science tools and techniques to build predictive models. Simplilearn’s Data Science training can help you learn all of its concepts from scratch.
In a Data Science course, you need to learn about so many concepts if you are a beginner or an intermediate. A Data Science course is a training program of around six to twelve months, often taken by industry experts to help candidates build a strong foundation in the field. Apart from the theoretical material, our online Data Science certification course includes virtual labs, industry projects, interactive quizzes, and practice tests, giving you an enhanced learning experience.
A Data Scientist is an individual who gathers, cleans, analyzes, and visualizes large datasets to draw meaningful conclusions and communicate them to the business leaders. The data is collected from various sources, processed into a format suitable for analysis, and fed into an analytics system where a statistical analysis is performed to gain actionable insights.
A question that I often hear from clients and colleagues is, "Why should I get a Data Science certification?" That is a fair question for most other areas of study and business. In areas such as finance or engineering, there are far more important accreditations you could and should achieve before “hanging your shingle” or trying to retool your skill set or career.
Data science is a broad discipline with a few accredited cetification programs. However, many of those programs are cost-prohibitive.
“There are at least 50 Data Science certification programs by universities worldwide offering degree and diplomas in this discipline,”writes data science blogger, Zeeshan Usman. “It costs from $50,000 to $270,000 and takes one to four years of your life.”
And although somewhat new in the nomenclature, data science encompasses many skills that professionals may already have acquired through work or educational experience such as:
Data scientists also need to have an understanding of and exposure to reproducibility, decision-making, and working with stakeholders and executives. So attaining a second (or third) degree may not be the best option for professionals looking to break into data science. Yet to be successful, they still need to communicate their experience, skills, and acquired knowledge to prospective employers.
Put yourself in the position of a hiring manager; say her name is Paula. Paula has a couple of full-time openings for a Data Scientist. She has done a lot of research and has decided to hire at an entry-level. The person she hires will need to work with her and her staff of data scientists, business analysts, data analysts, and business intelligence developers.
She has a stack of resumes to read through and she has several questions that need to be answered before she decides to set up phone interviews. However, Paula knows that curriculum vitae (CV) often do not align with the skills and experience needed for a Data Scientist position. She may see many CVs from college graduates, she may see many resumes from men and women with several years of work experience but without any practical data science experience. But since this is an entry-level position, she will likely not see any applicants with real knowledge in the field of data science.
So what should Paula focus on? How should she shortlist applicants for the phone interview? How can Paula know which of the applicants has a real, proven commitment to becoming a Data Scientist? She may very well focus on the resumes that list Data Science certifications along with any pertinent business experience! And if those certification programs have compulsory projects to complete, that’s even better. You can begin to build your portfolio of data science projects before ever landing a job.
Data science is a fast-growing field. According to an article by Forbes, IBM predicts the demand for data scientists will grow by over 25 percent by 2020. Budding Data Scientists need to get their resumes and CVs out there as soon as is practicable, but they still need to gain valuable experience with those data science skills mentioned above. Data Science certifications are the quickest way to learn and hone the skills and techniques necessary to land that first data science job.
Furthermore, Data Science certifications allow students to learn and hone skills that won’t normally be acquired through work experiences, such as exploratory analysis skills, visualization skills, and data mining/machine learning algorithms.
So get your certifications in R, Python, and SQL. Or learn Hadoop or Apache Spark. Take some statistics courses. Practice everything you learn, every day.
These Data Science courses 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. This Data Science certification training will make you learn R, Python, Machine Learning techniques, data reprocessing, regression, clustering, data analytics with SAS, data visualization with Tableau, and an overview of the Hadoop ecosystem.
Professionals who do not have any prior knowledge of the field can easily begin with this Data Science certification training course as you’ll gain a thorough knowledge of the basic concepts as well.