MCSA: Machine Learning Training & Certification Courses

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Machine Learning course has been planned by two expert Data Scientists so that we can share our information and benefit us study multifaceted theory, algorithms and coding libraries in a simple way. We will walk you step-by-step into the World of Machine Learning. With this course, we will progress new skills and advance our understanding of this stimulating yet lucrative sub-field of Data Science. Furthermore, the course is filled with practical exercises which are based on live samples. So not only we will learn the concept, but we will also get complete practice building our own models. This course includes both Microsoft R and Azure Machine Learning with hands-on practice.

Course Objectives:

  • Learn to analyze data using Azure Machine Learning and Microsoft R Techniques.
  • Become one of the most in-demand Data Scientists in the world today.
  • Learn how to analyze large amounts of data to bring out insights.
  • Relevant examples and cases make the learning more effective and easier.
  • Increase practical knowledge through the problem solving based method of the course along with working on a project at the end of the course

What is all involved in becoming an MCSA: Machine Learning?

There are three steps that are involved in becoming an MCSA: Machine Learning:

  • Skills – The prerequisites or the skills required for an MCSA: Machine Learning course include prior experience in Machine Learning, Data Science or Analytics.
  • Exams – The candidate needs to clear two specific exams namely:
    • Analysing Big Data with Microsoft R
    • Perform Cloud Data Science with Azure Machine Learning
    • It is imperative to explore the exam prep resources for better clarification and understanding.
  • Certification – Upon passing the two exams, the candidate earns an MCSA: Machine Learning certification.

MCSA: Machine Learning Certification Exams

Analysing Big Data with Microsoft R (Exam 70-773) - This certification is designed for candidates involved in processing and analyzing data sets larger than memory using R. The prerequisites for this exam are:

  • Prior experience with R
  • Knowledge of Data Structures
  • Understanding of basic programming concepts
  • Ability to write and debug R functions

The course is basically targeted at Data Scientists and Analysts.

Perform Cloud Data Science with Azure Machine Learning (Exam 70-774) - This certification is designed for individuals already using Azure cloud services to build and deploy intelligent solutions. The prerequisites for this exam include:

  • Familiarity with Azure Data Services and Machine Learning
  • Knowledge of common data science processes like filtering and transforming Data Sets, Model Estimation and Model Evaluation.
  • Experience in publishing effective APIs for knowledge intelligence

The course is aimed at professionals such as Data Scientists and Analysts.

Advancing Your Skills after Earning an MCSA: Machine Learning Certification

Upon earning your MCSA: Machine Learning certification, earn an MCSE in Data Management and Analytics to broaden and advance your skills.

MCSE: Data Management and Analytics is a certification that validates your skills in administering SQL, building data solutions and using business intelligence data, both on-premises and in cloud environments.

The target audience for this certification includes Database Analysts, Database Designers, and Business Intelligence Analysts.

Recommended Skills before Pursuing MCSA: Machine Learning Certification Course

It is highly recommended to earn an MTA certification before planning to achieve MCSA: Machine Learning certification.

Microsoft Technology Associate (MTA) certification is an entry-level certification associated with technology that caters to a number of technical concepts, demonstrates core technical knowledge and increases technical credibility.

The certification doesn’t require any prerequisite and is earned easily with only one exam.

Need more info ? Email  or   Enquire now!

MCSA: Machine Learning consist of following courses

Course # Course Name Exam # Duration (days)
20773A 20773A: Analyzing Big Data with Microsoft R70-7733
20774B 20774A - Perform Cloud Data Science with Azure Machine Learning70-7745
Total 8
Delivery Mode Location Course Duration Fees Schedule
Instructor-Led Online Training (1-on-1) Client's Home/Office8 Days $ 4,120 As per mutual convenience (4-Hours Evenings & Weekends Possible
Classroom Training * Dubai 8 Days $ 4,840 On Request
Delhi, Bangalore, Dehradun (Rishikesh), Goa, Shimla, Chennai 8 Days $ 3,444 On Request
Fly-Me-a-Trainer Client's Location8 Days On Request As per mutual convenience

MCSA: Machine Learning Benefits

On completion of this course, you will know:

  • Involved in Machine Knowledge
  • high school knowledge in math and want to start learn Machine Learning
  • Any intermediate level with basics of machine learning, together with the classical algorithms like linear regression or logistic regression,
  • Comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.
  • Enthusiastic in starting a career in Data Science.
  • Data analysts who want to level up in Machine Learning.
  • Satisfied with their job and who want to become a Data Scientist.
  • Whomsoever want to generate added value to their professional by using powerful Machine Knowledge in tools.

Give an edge to your career with Machine Learning certification training courses. Students can join the classes for MCSA: Machine Learning Training & Certification Course at Koenig Campus located at New Delhi, Bengaluru, Shimla, Goa, Dehradun, Dubai & Instructor-Led Online.

Recommended Courses and Certification:

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Verbatim Student Feedback

Q1 Say something about the Trainer? Q2 How is Koenig different from other training Companies? Q3 Will you come back to Koenig for training?

Student Name Country Month Feedback Rating
Shofolabo Gbenga Nigeria Jun-2019 A1 He passes the message easily and also patient in passing knowledge. Makes the class lively with other discussion
Agisheva Mira Kazakhstan Jun-2019 A1 Like simple examples
Emmanuel Assimeku Ghana Jun-2019 A1 He is very knowledgeable in his field, friendly and humble. He also makes the training session more practical. He loves to share every bit of his knowledge even if it is outside the scope of the training.
Saud Badr Baghlaf Saudi Arabia Jun-2019 A1 Actually she is one of the best trainers I had , and she always provides me with new ways of solving any problem I faced , and most important thing that she is friendly and knows how to deal with her student
Shashi Suman India Mar-2019 A3 Trainer (Vatan Joshi) is very knowledgeable and helpful. Extends hours to if requires. its been pleasure working with him and would like to connect with him again in future
Ved Prakash Singh India Mar-2019 A1 Good knowledge on the course and has helped a lot during the training. He supported in troubleshooting even on the laptop issues. Good communication skill and able to answer all the question with confidence and with the correctness. I am glad to have Vatan as my trainer for this training.
Jones Mwende Tanzania Mar-2019 Accomodation,Transport and Trainers and the labs
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Hello Koenig


What is Machine Learning?

Machine Learning is one of the applications of Artificial Intelligence that enables systems to act automatically and learn from experience, without being explicitly programmed.

Which programming languages are recommended most for Machine Learning?

1. Python 2. Java 3. R 4. C++ 5. C 6. JavaScript 7. Scala 8. Julia

Which language is the best for Machine Learning?

Python is a leader among other languages used for Machine Learning. It is followed by Java, R and C++.

Is Deep Learning the same as Machine Learning?

Deep Learning is a subset of Machine Learning, though they function differently. Here is a few major difference between the two. Machine Learning models need guidance time and again but deep learning models function on their own; Unlike Machine Learning, Deep Learning specializes in solving problems from end to end, hence, require huge amounts of data. Machine Learning breaks data into parts and solves them individually; Deep Learning algorithms require high end machines while Machine Learning algorithms are capable of working on low end machines.

What is the difference between Artificial Intelligence and Machine Learning?

Artificial Intelligence is a broader term, under which machines carry out tasks rather smartly whereas Machine Learning comes within Artificial Intelligence wherein machines act automatically and learn and improve by experience.

Why is Machine Learning so important?

Machine Learning saves time and money. It automates tasks that frees up a lot of time and allows professionals to focus on complicated decision-making that cannot be handled by machines.

What does a Machine Learning engineer do?

A Machine Learning engineer creates algorithms for machines so that they perform tasks automatically, implements Machine Learning algorithms to solve business problems and performs research to improve current products and practices.

How much does a Machine Learning engineer make?

A Machine Learning engineer earns an average salary of $100,956 per annum, as per a survey done by PayScale.

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