Microsoft certified Azure Data Fundamentals Exam DP-900
Microsoft certified: Data Analyst Associate Exam DA-100
Microsoft Certified: Azure Data Engineer Associate Requirements: Exam DP-200, DP-201 Azure Data Engineers integrate, transform, and consolidate data from various structured and unstructured data systems into structures that are suitable for building analytics solutions.
Microsoft Certified: Azure Data Scientist Associate Requirements: Exam DP-100 The Azure Data Scientist applies their knowledge of data science and machine learning to implement and run machine learning workloads on Azure; in particular, using Azure Machine Learning Service.
Microsoft’s MCSE- Data Management and Analytics
Big Data Professional Using SAS 9 Certification
Cloudera certified Associate Associate
CCA Data Analyst
CCA Spark and Hadoop Developer
Zabeel certified can do - 18 hrs without lab
CCP Data Engineer Exam
AWS Certified Data Analytics
Big Data and Data Science
Data Science Certifications
Data scientific research can be specified as a mix of maths, service acumen, tools, formulas and also artificial intelligence strategies, all of which aid us in learning the covert insights or patterns from raw data which can be of significant usage in the formation of big business decisions.
In data science, one bargains with both unstructured as well as structured information. That is, finding out the fads based on historical data which can be useful for present choices as well as discovering patterns which can be designed and can be made use of for predictions to see what points might look like in the future.
Data science course will help you to do the Practical Data Science with R Program is a blend of Data Science, Machine Learning and Deep Learning enabling the real-world implementation of advanced tools and models. The program is designed to give in-depth knowledge of Machine Learning concepts including the essentials of statistics required for Data Science and R programming. Data Science course participants will learn how to use R libraries like Dplyr, Ggplot2 and tidyr and essential Machine Learning, Data Analysis techniques, such as supervised and unsupervised learning.
Artificial intelligence and Machine Learning will impact all segments of daily life by 2025, with applications in a wide range of industries such as banking and financial services, transport and logistics, and healthcare. Expertise in this domain places is fundamental to the future workplace roles which are predicted to grow sharply into 2025 and beyond.
Learning Outcome of Data Science Training:
The Data Science course provides the entire toolbox the participant need to become a data scientist.
Statistics: Develop a deep understanding of the principles that underpin statistical inference: estimation, hypothesis testing and prediction.
R: Learn to program in R, Master R Studio and practice working with statistical data in R.
Data Science and Machine Learning: Get hands-on experience building and deriving insights from machine learning models using R and Microsoft Azure Machine Learning.
Data Visualization and Storytelling: Learn the art and science of data storytelling and achieve greater analytics impact.
Capstone project: This project will cover key aspects from exploratory data analysis to model creation and fitting. To complete this capstone project, participants will use cutting edge machine learning-based supervised and unsupervised algorithms like Regression, Support Vector Machine, and Tree-based algorithms in the domain of their choice. This will empower participants with a project that can be showcased to potential employers as a testament to Data Science expertise.
Who needs the Data Science with R course?
Aspiring data scientists, data analysts, technologists, software developers, academics and students.
Professionals working with data scientists, managing Data Science oriented projects, or investing in Data Science ventures.
Detailed Course Content:
Module 1: Introduction to Data Science, Fundamentals of Statistics