Data Science & Machine Learning Course(Classroom Training)
rAIse stands for rise with AI. Which offers an attractive mix of lectures, practical cases and group work supervised by the experts from Eduwaive Foundation and other Industry experts in AI & related technologies under fourth industrial revolution such as ML, IOT, NLP, Computer Vision, BlockChain, Video Analytics & Cloud Computing. Gains hands on exposure to key technologies.
- Enables to extract valuable information for use in strategic decision making by algorithms.
- Teaches Data Science concepts & process which are derived from Statistics, Machine Learning, Data Engineering and Big Data.
- Experience world-class training by an industry experts on the most in-demand Data Science and Machine learning skills.
This course is a part of rAIse programme, which offers an attractive mix of lectures, practical cases and group work supervised by the experts from Eduwaive Foundation and other Industry experts. Gains hands on exposure to key technologies.
Rudramuni Swamy - Program Management
Contact at – +91 83601 68458
Here are few courses that we run under rAIse
- Hands on Data Science & AI for beginners
- Machine Learning with Python and R
- Natural Language Processing with Python
- AI & Deep Learning with TensorFlow
- Big Data Hadoop and Spark Certification
- Data Analytics with R, Excel and tableau
- Cloud Computing Courses AWS certification
- Cloud Computing Courses GCP certification
- Cloud Computing Courses Azure certification
- Agriculture Data Driven Courses
Concepts taught in the course:
- Python for the Data Analysis
- Python for the Data Visualization
- Applied Machine learning
- SQL, Big Data and Spark with Python
- Neural Networks and Deep Learning
- Introduction to Google Cloud
- Introduction to AWS Cloud Platform
- Basics of Software Development
For full course outline please click here
Practical Information about course
- The course fee for students – Rs. 6500 + 18%GST & for Industry Professional – Rs. 7500 + 18%GST – per person. The course fee includes course materials in soft copy (Note : Carry your own laptop with data modem)
- Group discounts also available
- Last date for registration – 19/09/2019
- Maximum number of participants – 10
- Course starts from – 21/09/2019 and lasts upto – 13/10/2019 (Weekend Course. For more information click here)
- Timings – 10:00AM to 4:00PM
Mr.Puneet Jindal – Chief Data Scientist
He is ISB, Hyderabad CBA alumnus and comes with more than 9 years of experience with 5 years as core Data Science experience in banking, e-commerce, logistics, travel etc
A PEC alumnus, with more than 13 years of industry experience in Startups & Corporates. He is a polyglot and has been involved in creating an architecture of BigData and ML projects for Telecom, Banking, Travel etc
A Product Visionary with MBA from SYMBIOSIS and was initial member of “Products & Strategy team’ at LENSKART. Out of total 8 years of Industry experience 5 years were into Product Strategy, Product Validation, Design, User Experience, Go to Market Strategy. Having rich experience in domains like e-commerce, Social-Media, Manufacturing, Automobile, Information technology along with Six-Sigma Green belt Certification from KPMG
He comes with 3+ years of full-stack data science experience in industry along with academia who is an open minded developer and technical lead & leaves no stone unturned for what is possible.
A Data Analyst with expertise in Machine Learning concepts, he often ties different fields together to get a new way ! He has worked in Big Data solutions around Hadoop, Spark, building full scale ETLs and also incorporating Machine Learning. Visualizing and getting insights out of data is also his forte!
Ambitious learner and Big Data Explorer, she has mastered Business Analytics from Arizona State University. Earlier worked on a few client projects and has hands on experience in Python, R, NLP etc. She understands that you can sell your product not just by technical expertise but by using story telling for communication.
Richmond upon Thames, Greater London, United Kingdom.