Study Data Science from IBM, University of California, University of Michigan & Georgia Tech by paying only for one!
IBM is named a Leader in the 2021 Gartner Magic Quadrant for Data Science and Machine Learning Platforms
University of California, Irvin’s program is intended for professionals in a variety of industries and job functions who are looking to help their organization understand and leverage the massive amounts of diverse data they collect. Others who would benefit from this program include: data engineers, data analysts, computer scientists, business analysts, database administrators, researchers, and statisticians.
University of California, Irvin’s program covers a wide array of topics in data science including data-driven discovery and prediction, data engineering at scale (inspecting, cleaning, transforming, and modeling data), structured and unstructured data, computational statistics, pattern recognition, data mining, data visualization, databases, SQL, Python, and machine learning.
University of Michigan has very comprehensive course to cover all below three
- Analysis Methods (AM): Understanding of core Data Science principles, assumptions & applications
- Data Management (DM): Data management, computation, information extraction & exploratory analytics
- Algorithms and Applications (AA): Hands-on experience with modeling tools and technology using real data
University of Michigan has an overarching goal of this Data Science Certificate Program to train a cadre of skillful data scientists with significant multidisciplinary knowledge, broad analytical skills and agile technological abilities. The program emphasizes the practice of modeling using modern technology to handle large, incongruent, and heterogeneous collections of data.
The latest Gartner Magic Quadrant for Data Science and Machine Learning Platforms has just been released, and IBM is delighted to be recognized as a Leader in the space. Gartner acknowledges that IBM Watson Studio on IBM Cloud Pak for Data “delivers a modern and comprehensive solution” for organizations seeking to more efficiently run and manage AI models, simplify their AI lifecycle management, and empower their data scientist with technology that can help optimize their data driven decision making.
Master Data analytics, networking, data storage, Big Data and Machine Learning on popular cloud platforms such as IBM, University of California Irvin, University of Michigan & Georgia Tech in single one course by KrackiN.
With the rising demand for cloud data technologies, the pay scale of these jobs is also increasing rapidly in the market. You will find better-paid jobs in data science computing. The average salary for a cloud computing professional at mid-level is Rs. 20-30 Lakh per annum.
Cloud data administrator
These experts manage a company’s cloud presence and infrastructure.
Cloud Data Engineer
A cloud data platform engineer is responsible for any technical duties associated with cloud computing such as design, planning, management, maintenance and support.
Cloud Data Developer
These professionals are responsible for programming solutions for the Cloud data, including automation, orchestration, and integration.
Data scientists work across a variety of tech fields, but in the cloud computing realm, they often focus on improving data quality and searchability as well as enabling machine learning (ML) and artificial intelligence (AI) solutions in the cloud.
Data Security Administrator
Jobs typically consist of making and implementing data security strategies both internally and in partnership with cloud data service providers in addition to monitoring systems for potential threats.
Cloud Data Strategist
They are responsible for overseeing a company’s cloud adoption plans, cloud data application design, and cloud data management and monitoring.
Master the core skill sets required to design, deploy and deliver data science services over the cloud such as analytics, networking, data storage, Big Data and Machine Learning on popular cloud platforms.
KrackiN has world’s Best Data Science Computing Instructors as below
Senior Data Scientist
Aije Egwaikhide is a Data Scientist at IBM who holds a degree in Economics and Statistics from the University of Manitoba and a Post-grad in Business Analytics from St. Lawrence College, Kingston. She is currently pursuing her Masters’s in Management Analytics at Queens University.
Ph.D., Data Scientist
Alex Aklson, Ph.D., is a data scientist in the Digital Business Group at IBM Canada. Alex has been intensively involved in many exciting data science projects such as designing a smart system that could detect the onset of dementia in older adults using longitudinal trajectories of walking speed and home activity.
Amalia B. Stephens
Georgia Tech Language Institute
Education: M.A.T., Emory University. Amalia Stephens has developed and taught a wide variety of classes at the GA Tech Language Institute for more than seven years. She also taught English in the Fulton County Georgia Public School System and in Cairo, Egypt, and the Central African Republic. Prior to teaching, Amalia worked as a business writer in New York and Atlanta for newspapers, business publications, and private companies.
School of Information
Daniel Romero is an Assistant Professor with the School of Information at the University of Michigan. His main research interest is in the empirical and theoretical analysis of Social and Information Networks with a particular interest in understanding the mechanisms involved in network evolution, information diffusion, and user interactions on the Web.
Hima Vasudevan is a Data Scientist in the Digital Business Group at IBM. She is part of the Cognitive Class team and focuses on creating skills offerings and deliver learning curriculum for the Data Science and Data Engineering professions.
Ph.D., Data Scientist at IBM
IBM Developer Skills Network
Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.
Margaret Meloni, MBA, PMP
Instructor, University of California, Irvine Division of Continuing Education
Margaret Meloni is President of Meloni Coaching Solutions, Inc., a company devoted to helping you successfully navigate the human side of the project world. Margaret has supported project managers at organizations such as Occidental Petroleum, Northrop Grumman, Toyota Motor Credit, Southern California Edison, CalStart, and arc.
Senior Developer Advocate with IBM Center for Open Data and AI Technologies
Senior Developer Advocate with IBM Center for Open Data and AI Technologies, Svetlana has been a software engineer and technical lead for SPSS for many years. She works on open standards for machine learning model deployment PMML and ONNX
Ph.D., Data Scientist and Developer
Yan Luo, Ph.D., is a data scientist and developer at IBM Canada. Yan has been building innovative AI and cognitive applications in various areas such as mining software repositories, personalized health management, wireless networks, digital banking, etc. Yan received his Ph.D. in Machine Learning from the University of Western Ontario.