Things you will learn……
Why ExcelR ?
About Certified Data Scientist Training Program
Introduction to Data Science Certification Training
ExcelR offers 120 hours classroom training on Business Analytics / Data Scientist / Data Analytics. We are considered as one of the best training institutes on Business Analytics in Hyderabad. “Faculty and vast course agenda is our differentiator”. The training is conducted by alumni of premier institutions such as IIT & ISB who has extensive experience in the arena of analytics. They are considered to be one of the best trainers in the industry. The topics covered as part of this Data Scientist Certification program is on par with most of the Master of Science in Analytics (MS in Business Analytics / MS in Data Analytics) programs across the top-notch universities of the globe.
Our Business Analytics certification training course is designed by the industry experts, which is precisely tailored for the professionals who wants to pursue a career as a Data Scientist in job market. We offer a comprehensive placement program where we equip you with hands on training on Business Analytics, resume preparation, case studies, Live projects, mock interviews etc. We do the necessary hand holding till the participants are placed in a job in the field of Analytics.
What is Business Analytics / Data Analytics?
Business Analytics or Data Analytics is an extremely high-in-demand profession which requires a professional to possess sound knowledge of analyzing data in all dimensions and uncover the unseen truth coupled with the logic and domain knowledge to impact the top-line (increase business) and bottom-line (increase revenue).
Also Google Trends shows the upward trajectory with an exponential increase in volume of searches like never seen before. This is proof enough to back the statements made by Harvard Business Review and the business research giants, that Business Analytics will be the most sort after professional world has ever witnessed.
What is a Data Scientist? Or Rather Who is a Data Scientist?
Data for a Data Scientist is what Oxygen is to Human Beings. This is also a profession where statistical adroit works on data – incepting from Data Collection to Data Cleansing to Data Mining to Statistical Analysis and right through Forecasting, Predictive modeling and finally Data Optimization. A Data Scientist does not provide a solution; they provide most optimized solution out of the many available.
Gartner predicted in 2012 that Data Scientist & Business Analytics jobs will increase to the tunes of Millions by the end of 2015. This is very evident with the rise in job opportunities in various job portals. As a Data Scientist or an aspirant you should not believe us. Go! research for your own and confirm the facts and figures.
Who should do Business Analytics Course
Professionals who can consider Business Analytics / Data Analytics Certification Training as a next logical move to enhance in their careers includes:
- Professionals working on Business intelligence & reporting tools
- Professionals working on Data warehouse technologies
- Statisticians, Economists, Mathematicians
- Software programmers (they have an edge in writing code to accomplish a prediction/classification/forecasting model)
- Business analysts (they have an edge in terms of industry/sector/domain experience)
- Six Sigma consultants who already have exposure to statistics
- Freshers (market demand is thriving organisations to hire the freshers trained on analytics)
How to become a Data Scientist?
Accrue knowledge on dealing with data by getting trained and/or certified by any of the well-known institutes which have rich experience working closing with the ever evolving industry.
Knowing data analytics tools or data mining software alone will not help you analyze data.
So WHAT else is required?
One should possess Domain/Sector/Industry knowledge and learn relevant concepts to strike the right nail. A few such examples which are not limited to those mentioned are:
- One into web development might want to learn Web Analytics
- One into search engine optimisation might want to learn Social Media Analytics & Website Analytics
- One into sales & marketing might want to learn Marketing Analytics, Customer analytics, Twitter Analytics, Facebook Analytics, Social Media Analytics, Data Collection tools
- One into human resources might want to learn Workforce Analytics
- One into health care might want to learn Healthcare Data Analytics
Real world problems
Life Sciences & Health Care – Wearable Devices
- Many people across the globe are wondering on how to predict diseases very early so that changing lifestyle habits will cure the disease instead of medication. For this people started wearing health bands, a few call them sports band which is used to track heart beat rate, calories burnt, sleeping patterns, number of steps taken (walked) and many more. Jawbone is the most famous wrist band and its users have helped generate about 130 million nights of sleep and experts call it the biggest sleep study on the planet. Also recorded are about 1.6 trillion steps and 180 million items of food.
We can tag the data to our personal doctor who will monitor and inform us on what diseases we are likely to be infected with and what precautions should be taken to avoid it. Sounds WOW!
Retail – Location Based Analytics
- Thousands of footfalls are witnessed in any known shopping mall across the globe. Can the store owners within the mall convert the footfalls into revenue? Answer is ‘YES’! The moment a person connects to free wi-fi available in the mall, a unique MAC address is assigned to the person. From there on the details such as time spent in a store, speed of movement (moving across the wifi zones/range), past buying behaviour, number of times a person visited a store versus number of times purchase happened and various other parameters are gauged, to send a personalised coupon which will lure the potential customer to become a source of revenue.
Number of coupons sent versus number of purchases & Number of coupons sent versus amount purchased are the key Business metrics captured & evaluated to enhance the prediction model. Amazing, isn’t it!
Watch out this space for interesting use cases…..
Data Analytics, Business Analytics & Data Science are the same with just 2 different names. The name of the role of people working in this profession is called as Data Scientist
Data analytics is a profession which caught the attention of the world only since 2 years. Because of this very reason most companies are struggling to close the demand-supply gap. Hence, people who are trained and have decent exposure towards the data analytics techniques are recruited immediately.
There are a lot of job opportunities in various job portals for freshers. The key thing employer would be keen to know is whether you have the conceptual knowledge or not. The projects provided by ExcelR in various concepts will only reinforce your learning to make you market ready for the jobs.
We understand that human brain can grasp only so much. Hence, we record all the sessions and provide access to the e-learnings to the trainees for the rest of their life.
Yes and No. Yes in the sense programming skills would be required & No in the sense one need not have extremely strong programming skills. However, we at ExcelR ensure that you get sufficient exposure on the statistical programming tool called ‘R’. We start right from the basics assuming you do not have any exposure towards programming.
R has approximately 50% market share & it is open source (free of cost). Hence, R is very lucrative in the analytics space. Almost all the jobs are asking for experience & exposure in R. Demand for other statistical tools is decreasing steadily & hence it is recommended to be futuristic and invest time in learning R.
Salaries range varies based on experience, industry, domain, geography & various other parameters. However, as a general thumb rule, we can apply the following formula:
Salary = No. of years of experience * 3 Lacs per annum (India – INR)
Salary = No. of years of experience * $ 1200 to $1500 per annum (Overseas – USD)