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Machine Learning Courses Learner's Reviews

  • Hans Friedhoff

    Hans Friedhoff

    Senior Manager, Digital Communications

    After completing the bootcamp, I transitioned to a Machine Learning Engineer within my organization. I was also able to obtain an 18% salary increase.

  • Fritz Canon

    Fritz Canon

    Project Manager Business Development

    My overall experience with Simplilearn was extremely positive and enriching. One aspect that stood out to me was the comprehensive curriculum offered by Simplilearn. The course content was well-structured and covered all the essential topics related to my chosen field of study.

  • Tony Vigna

    Tony Vigna

    The overall experience was outstanding. Since I am a working professional, I enjoy a flexible schedule. The classes were on weekends and did not collide with the working hours. So, it was conducive. The best part is that they take feedback regularly and work on it to improve the learning experience for the students.

  • Anthony Palomba

    Anthony Palomba

    Simplilearn’s course turned out to be the best decision of my life. I joined a marketing firm as a consultant and a permanent position at my university with a 35% salary increment. Moreover, I can execute my knowledge in my teaching and research.

  • Diego Sabajo

    Diego Sabajo

    Co-Founder

    My learning experience with Simplilearn was outstanding. The course material is very thoughtfully designed. The way of explaining was simple and easy to understand. The instructors were good; the support was really helpful. I recommend this course to others who want to start something in the AI domain.

  • Abhineet Srivastava

    Abhineet Srivastava

    This course was all worth it! The course content was comprehensive and updated. The journey from a Python-based approach to understanding Statistical concepts, Machine Learning, and other concepts was just incredible. Thanks to all the amazing trainers and co-learners for giving me such an enriched experience.

  • Filipe Theodoro

    Filipe Theodoro

    Machine Learning Engineer

    This course gave me the basic knowledge required to start building my own models, from organizing and selecting the data to run and testing the models. Also, the trainers were very clear when explaining and gave us lots of tips.

  • Shailender Kumar

    Shailender Kumar

    The Deep Learning with Tensorflow course was handled very well by Mr. Shivendra Kumar. He took many pains to advance this highly technical course and answered all students’ questions (even multiple times) clearly without compromising the quality of the training. I recommend this course and the faculty.

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FAQs on Machine Learning Courses

  • What are the highest paying Machine Learning Certificates?

    ML is a popular course, especially in developed nations. To set up a flourishing career in this domain, learners must possess machine learning certifications. It is a prerequisite to significant earnings and a position in a reputable firm. Whether a student or a skilled individual, the recognition enhances job prospects.

    Since this industry is expanding swiftly, it has given many employment prospects for dedicated students. If they wish to know about the highest-paying Machine Learning credentials according to earnings, check this table:

     

    CERTIFICATE OFFERING COMPANY AVERAGE EARNINGS EXPENSE
    IBM Recognized Expert - AI Industry Workflow V1

    IBM Enterprise

    $173,600

    $200

    Azure AI Engineer Assistant

    Microsoft Enterprise

    $164,770

    $165

    Proficient Machine Learning Expert

    Google Inc.

    $112,710

    $200

    AWS Recognized Machine Learning - Profession

    Amazon

    $97,360

    $300

    IBM Recognized Data Science Course - ML Expert V1

    IBM Enterprise

    $97,360

    $200

  • Which language should I learn first - AI or ML?

    Machine Learning is a component of Artificial Intelligence involving the designing and distribution of data from past statistics and references. It teaches computers by feeding information and statistical approaches to assist them in improving their job. AI for decision-making is the simulation of mortal intellect procedures through computers. Its apps comprise expert systems, NLP, speech knowledge, and Machine Learning.

    Learners must understand that Machine Learning comes under Artificial Intelligence. It means if they wish to excel in data science, begin with the best machine learning course. The online course will enhance your performance and accuracy of Machine learning techniques, design workflow, and create a portfolio to resolve business complexities and optimize production.

  • What are the best machine learning courses?

  • Is R or Python better for Machine Learning?

    If learners have no idea which machine learning certifications are ideal for employment growth, the following table will help clear the doubts.

     

    Basis of Difference

    R

    Python

    Nature of PL

    Statistical

    General purpose

    Degree of Adaptability

    It is extremely rigid.

    It is quite adaptable.

    Suitability

    It is ideal for statistical research and data intelligence.

    It is ideal for various jobs such as web development, input manipulation, and ML.

    Ease of Understanding

    It is a little difficult to understand because of the complex syntax.

    It is simpler to comprehend because of the relatively simple syntax.


    Although both languages are open-source, Python is universally a more effective language. On the other hand, R’s scope is confined to statistical analysis. Since both languages are nearly identical, the selection relies on the preference and employment needs.

    However, it has been observed that Python performs adequately in input manipulation and monotonous jobs. It is a more suitable choice if willing to create a virtual device based on Machine Learning. But if the desire is to construct a machine for ad-hoc research, R is a better choice.

  • Which Coding language is highly relevant for Machine Learning?

    Machine Learning is a complicated but fascinating domain. Several data engineering and analytics experts have dedicated their jobs to comprehending it. Since plenty of programming expressions are accessible, it is tough to pick the most suitable one. But, we have made the decision easier by specifying the 5 best machine learning courses, high in demand, at the moment.

    R

    It is a practical language adopted by statisticians and analysts to analyze and visualize inputs. It can consolidate data-heavy ML jobs and uphold other expressions.

    C++

    It is an object-oriented dialect perfect for performance-critical assignments and memory manipulation. Since it operates at a lower level, it can connect with computers in their aboriginal codes and provides a steeper knowledge arc.

    Java

    This language is among the machine learning courses with a complex syntax, ideal for constructing varied types of applications that can work on any medium.

    JavaScript

    It is a superior-style language that grew into a general-purpose dialect within a few years. It is ideal for fronted jobs and stretches to the backend in the form of an API.

    Python

    It is another superior programming language whose reputation has spiked in the last few years. It has straightforward syntax and increased speed which makes it perfect for rapid prototyping and the favorite of Machine Learning practitioners and data analytics professionals.

     

  • How do AI and ML differ from each other?

    AI and ML courses are valuable for companies of all scopes and are employed in multiple ways to automate repeated processes. Although they have many similarities and are used in similar industries such as healthcare, manufacturing, retail, telecommunications, and financial services, they are not identical.

    If learners want to know how these languages vary from each other, check the following table:

     

    Basis of Difference

    Artificial Intelligence (AI)

    Machine Learning (ML)

    GOAL

    Its goal is to build a machine that can mimic human intelligence.

    It aims to teach a machine the art of performing a specific task and generating outcomes by determining the patterns.

    EXTENT OF SCOPE

    It has a broader scope.

    It has a narrower scope.

    WORKING CAPACITY

    It can work with structured, unstructured, and semi-structured data.

    It can only work with structured and semi-structured data.

    RELIANCE

    These systems rely on logic and decision trees to learn.

    These systems rely on statistical models to learn.

  • Is Coding necessary for Machine Learning?

    To pursue a profession in Artificial Intelligence and Machine Learning, students must learn the art of coding, as both languages execute via coding. If they know how to implement a code, it will give them a better grasp on the operation, monitoring, and optimization of algorithms.

    Out of R, C++, Java, Python, JavaScript, Prolog, and Lisp, students can learn any ML through the best machine learning course, depending on the industry they are working in. But, learn about the underlying concepts of Machine Learning before starting with coding.

  • How to get a Machine Learning Certification?

    To obtain machine learning certifications, they must appear for and clear the two hours examination. It includes around 50 to 60 MCQs, covering topics such as framing ML general issues, structuring solutions, and creating various models. This certification is valid for two years. When this duration is over, they must re-appear for the exam to maintain the certification.

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