Deep Learning & Artificial Intelligence
Things you will learn……
Why ExcelR ?
About Advanced Analytics Certification Training
ExcelR offers 60 hours classroom training on Advanced 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 Advanced 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.
- Course content is designed & training is delivered by IIT, ISB alumni who have immense experience in building AI and Deep Learning system solutions
- Algorithms and concepts will be explained with a blend of theory & practicals by including a real life case study for each concept explained
- On successful completion of course, participants will get an opportunity to take part in designing solutions & implementing the same to solve real world problems
- Learn the de-facto tools used in the space of deep learning & advanced analytics. Tools include Python, R, XLMiner, Minitab, @Risk, OpenCV
- Complete support on the first live-project, you work at your work place
Introduction to Advanced Analytics Certification Training
Gartner, a top notch technology research firm, defines advanced analytics as the process of examination of huge volumes of data using sophisticated techniques & tools with or without human intervention, to discover deeper insights!
It is quite unlikely to be able to perform these tasks using traditional approaches for drawing deeper insights on the humongous, find pattern recognition from the complex, hidden data
In dealing with ‘Big Data Analytics’, where raw data is largely unlabelled and uncategorised, we must have tools and data visualisation technologies along with advanced analytical skills & expertise in deep learning to be able to solve problems and find new opportunities.
Organisations are collecting enormous amounts of domain-specific data from various sources of live-feed.
Crunching data of this magnitude needs special skills & analytical capabilities.
Using Advanced Analytics and Deep Learning techniques one can solve a lot of complex problems that are otherwise not possible. A few such examples are:
- Research in areas where human lives are at high risk can be avoided with the application of Deep Learning concepts
- Reducing manual intervention in some core areas would result in improved productivity is quality
- Fraud detection can be done using Deep Learning, helping many organisations take appropriate strategic decisions in least amount of time
- Using Neural Networks, customer recommendations are efficiently carried out
- Image processing and tagging, Voice recognition system, search engines, customer recommendations, customer relationship management, are all areas which can be improved using advanced analytical techniques
- Live-feeds is being dynamically read and understood by deep learning concepts
Industries are on a lookout for resources with Advanced analytics skills who have hands-on experience working with Deep Learning algorithms. There is a huge concern on the lack of skilled resources with Advanced analytics and Deep Learning skill-set.
According to the report published by Zion Market Research, the estimated growth for advanced analytics in the global market would be around 50% by 2021. This is a huge increase in market value since 2015 when the market value was around USD 10.70 billion.
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)