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  • IABAC®  Global Certification
  • 2-Month | 80 Learning Hours
  • 20-Hour Live Online Training
  • 5 Capstone Projects
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

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  • Self Learning + Live Mentoring
  • IABAC®  Global Certification
  • 1 Year Access To Elearning
  • 5 Capstone Projects
  • Job Assistance
  • 24*7 Learner assistance and support

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The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

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Why DataMites Infographic


  • What is Machine Learning
  • Applications of Machine Learning
  • Machine Learning vs Artificial Intelligence
  • Machine Learning Languages and platforms
  • Machine Learning vs Statistical Modelling
  • Popular Machine Learning Algorithms
  • Clustering, Classification and Regression
  • Supervised vs Unsupervised Learning
  • Application of Supervised Learning Algorithms
  • Application of Unsupervised Learning Algorithms
  • Overview of modeling Machine Learning Algorithm : Train , Evaluation and Testing.
  • How to choose Machine Learning Algorithm?
  • Simple Linear Regression : Theory, Implementing in Python (and R), Working on use case.
  • Multiple Linear Regression : Theory, Implementing in Python (and R),
  • Working on use case.

  • K-Nearest Neighbors : Theory, Implementing in Python (and R), KNN advantages, Working on use case.
  • Decision Trees : Theory, Implementing in Python (and R), Decision |Tree Pros and Cons, Working on use case.
  • Random Forests : Theory, Implementing in Python (and R), Reliability of Random Forests, Working on Use Case.
  • Naive Bayes Classifier: Theory, Implementing in Python (and R), Why Naive Bayes is simple yet powerful, Working on use case.
  • Support Vector Machines: Theory,Support vector machines with Python and R, Improving the performance with Kernals, Working on Use Case.
  • Association Rules: Theory, Implementing in Python (and R),Working on use case.
  • Model Evaluation: Overfitting & Underfitting
  • Understanding Different Evaluation Models
    • K-Means Clustering: Theory, Euclidean Distance method.
    • K-Means hands on with Python (and R)
    • K-Means Advantages & Disadvantages
    • Hierarchical Clustering : Theory
    • Hierarchical Clustering with Python (and R)
    • Hierarchical Advantages & Disadvantages
    • Dimensionality Reduction: Feature Extraction & Selection
    • Principal Component Analysis (PCA) : Theory, Eigen Vectors
    • PCA example with Python (and R) with Use case
    • Advantages of Dimensionality Reduction
    • Application of Dimensinality Reduction with case study.
    • Collaborative Filtering & Its Challenges





Machine Learning (ML) is a different approach where the computer learns the rules of solving complex problems without being explicitly programmed. Machine Learning algorithms are at the core and important pieces of data science.

This course - Machine Learning Foundation, is designed to provide a holistic understanding of various ML algorithms with high-level theory and hands-on application of ML algorithms to classic data sets.


Machine Learning (ML) is a different approach where computer learns the rules of solving complex problems without being explicity programmed. Machine Learning algorithms are at the core and important pieces of data science.

This course - Machine Learning Foundation, is designed to provide a holistic understanding of various ML algorithms with high level theory and hands on application of ML algorithms to classis data sets.

  • Introduce Machine Learning with a holistic approach.
  • Discuss high-level theory of popular Machine Learning Algorithms
  • Hands-on coding of popular ML algorithms on classic data sets
  • Access the knowledge through the International Association of Business Analytics (IABAC™) framework.
  • Introduce Machine Learning with wholistic approach.
  • Discuss high level theory of popular Machine Learning Algorithms
  • Hands on coding of popular ML algorithms on classic data sets
  • Access the knowledge through International Association of Business Analytics (IABAC™) framework.

In recent years, Machine Learning has taken over a mainstream business and evolved has a career track by itself. A quick search in job portals reveals about 20,000 Machine Learning job opportunities on a daily basis in the USA alone. This course lays a solid foundation for ML aspirants with high-level theory and concept along with hands-on coding of popular Machine Learning algorithms: Linear and Logistic Regression, K-means clustering, SVM (Support Vector Machines), KNN (K -Nearest Neighbours) and Neural Networks.

This course is a foundation level course, so most of the aspiring Machine Learning candidates can opt for this course


  • Professionals aspiring to pursue a career in Machine Learning or Data Science in general
  • Fresh college graduates, who are looking to career options in Data Science
  • Senior professionals, who want to gain a solid foundation on Machine Learning to manager Data Science projects
  • Candidates pursuing Data Scientist tracks

This course provides a solid foundation in Machine Learning as the syllabus is aligned with international market requirements. The candidates attending this course gain the right perspective on ML rather than getting lost in the ocean of articles and tutorials on the internet. As a part of the course, a certification assessment is conducted and candidates achieving minimum qualifying score receive a global certification, carrying immense value of the testimony of their ML knowledge.

At DataMites™, we truly believe and very excited about this big wave of Data Science. DataMites™ work with globally renowned Machine Learning experts in designing as well delivering training course. There are millions of jobs and business opportunities in Data Science across the globe as of today and this is only going to increase exponentially in the coming years.

DataMites is founded by a group of passionate Data Science evangelists with decades of experience in Analytics, big data and Data Science working with fortune 100 companies, across the globe. The mission of DataMites™ is to enable data science professionals with strong data science skills aligned market requirements and be a part of this phenomenal Data Science era.


  • PASSIONATE: We are passionate about enabling professionals with best practice Data Science skills
  • ACCREDITED: DataMites™ is accredited with "International Association of Bussiness Analytics Certifications (IABAC™)", aligning the syllabus with global market requirements
  • HANDS-ON PROJECTS : On course completion, worthy candidates are involved in consulting assignments at building block levels to provide real-time exposure, thus supporting them to gain the confidence to work in real-world Data Science projects
  • JOB ASSISTANCE: A dedicated team, Placement Assistance Team (PAT), is tasked to assist candidates in preparing for the first Data Science job and mapping the job requirements to the  individual candidate profile.
  • FLEXIBLE LEARNING: DataMites™ provides flexible learning options from traditional classroom to Virtual classroom, Instructor-led online and self-learning.
  • LIBRARY: A Data Science library with a collection of valuable Data Science books and publications, assisted check-in/check-out options.
  • DATA SCIENCE LAB: Access to Cloud Data Science lab with popular platforms, R, Python, Tensorflow etc.,

Machine learning refers to a subset of artificial intelligence where machines can imitate intelligent human behavior.

Machine learning is crucial for businesses as it helps unlock the value of data, enabling better decision-making and gaining a competitive edge.

Machine learning has become pervasive across various industries, with virtually every sector relying on data for insights and decision-making.

Machine learning algorithms are categorized into supervised, semi-supervised, unsupervised, and reinforcement learning.

Machine learning finds applications in diverse fields such as medical, finance, social media, facial and voice recognition, online fraud detection, and biometrics. The global machine learning market is projected to reach $8.81 billion by 2025.

Job roles in machine learning include data scientist, machine learning engineer, machine-learning scientist, NLP scientist, software engineer, software developer, business intelligence developer, computational linguist, human-centered machine learning expert, application architect, and data analyst.

Machine learning certification programs are open to individuals interested in learning machine learning, regardless of their level of expertise. Those aspiring to build a career in data analytics would greatly benefit from these courses.

Prerequisites for machine learning include a good understanding of applied mathematics, basics of computer science, communication skills, knowledge of NLP and neural networks, and strong problem-solving abilities.

Learning machine learning is no more difficult than mastering any other programming libraries. The focus should be on applying the algorithms rather than inventing them. With proper guidance, machine learning can be learned easily, leading to a rewarding career.

Artificial intelligence (AI) aims to develop computer systems that can think like humans. Machine learning is a subset of AI that focuses on machines learning from data without explicit programming.

Freshers can find job opportunities in machine learning by acquiring the necessary skills and networking with experienced professionals in the field.

The average annual salary of a Machine Learning Engineer is around  $156,885 in the United States, £60,885 in UK, and INR ₹8,47,730 in India. (Indeed)

Machine learning certifications are valuable credentials that demonstrate expertise in the field, increasing job prospects in a technology-driven world.

Machine learning is a form of artificial intelligence that enables computers to make accurate predictions without explicit programming. Its promising potential makes it a significant technology for the future.

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DataMites™ provide flexible learning options from traditional classroom training, lastest virtual live classroom to distance course. Based on your location preference, you may have one or more learning options

This course is perfectly aligned to the current industry requirements and gives exposure to all latest techniques and tools. The course curriculum is designed by specialists in this field and monitored improved by industry practitioners on continual basis.

All certificates can be validated with your unique certification number at portal. You also get candidate login at , where can find your test results and other relevant validation details.

The results of the Exam are immediate, if you take online test at portal. The certificate issuance, as per IABAC™ terms, takes about 7-10 bussiness days for e-certificate.

No, the exam fees are already included in the course fee and you will not be charged extra.

Course fee needs to be paid in one payment as it is required to block your seat for the entire course as well as book the certification exams with IABAC™. In case, if you have any specific constrains, your relation manager at DataMites™ shall assist you with part payment agreements

DataMites™ has a dedicated Placement Assistance Team(PAT), who work with candidates on individual basis in assisting for right Data Science job.

You get 100% refund training fee if you the training is not to your satisfaction but the exam fee will not be refunded as we pay to accreditation bodies. If the refund is due to your availability concerns, you may need to talk to the relationship manager and will be sorted out on case to case basis

DataMites™ provides loads of study materials, cheat sheets, data sets, videos so that you can learn and practice extensively. Along with study materials, you will get materials on job interviews, new letters with latest information on Data Science as well as job updates.

To learn Machine Learning, you can enroll in the Machine Learning Courses provided by DataMites. They offer comprehensive training for individuals looking to build a career in this field.

DataMites offers the following Machine Learning certifications:

  • Machine Learning Expert
  • Machine Learning Foundation
  • Machine Learning Tensorflow
  • Machine Learning with R
  • Machine Learning with Python

For beginners, the Machine Learning Foundation course is highly recommended.

The Machine Learning Foundation course provides a comprehensive understanding of Machine Learning, including its concepts, theories, and practical implementation of ML algorithms.

The ML Foundation course covers:

  • Introduction to Machine Learning
  • High-level theory of popular Machine Learning algorithms
  • Hands-on coding of common machine learning techniques on well-known datasets

The ML Foundation course offers several benefits, including a solid foundation in Machine Learning aligned with international market standards. It provides a structured learning approach and a certification evaluation, leading to a globally recognized certification.

The ML Foundation course is suitable for:

  • Individuals interested in a career in Machine Learning or Data Science
  • Recent college graduates seeking jobs in the field of data science
  • Senior professionals looking to manage Data Science projects and gain a solid foundation in Machine Learning
  • Candidates aspiring to become data scientists
  • DataMites holds international accreditation for Machine Learning as an institute certified by the International Association of Business Analytics Certification (IABAC).
  • They have a large student base, with over 25,000 enrolled learners.
  • DataMites provides a three-step learning method, including self-study materials, live online training, and real-world projects.
  • Successful completion of the training leads to an IABAC certification, globally recognized in the industry.
  • DataMites offers internship opportunities with AI company Rubixe, a global technology firm.

The fee for the machine learning foundation course online varies depending on the region:

  • USA: $340 (Discounted price: $286)
  • India: INR 21,000 (Discounted price: INR 17,323)
  • Europe: 330 GBP (Discounted price: 163 GBP)

DataMites offers flexible learning options, including live online training, self-learning methods, and classroom training. You can choose the method that suits your availability.

Flexi-Pass provides you with three months of access to sessions at DataMites. You can utilize this time for query resolution and revision.

Upon completing the training, DataMites will issue an IABAC® certification that holds global recognition for your relevant skills.

Yes, upon successful completion of the course, you will receive a Course Completion Certificate from DataMites.

Yes, DataMites offers classroom training, currently available in Bangalore. However, they can consider hosting sessions in other locations based on demand and the availability of candidates.

Yes, DataMites provides a free demo class to give you an overview of the training and an understanding of what will be covered.

DataMites accepts payments through cash, net banking, checks, debit cards, credit cards, PayPal, Visa, Mastercard, and American Express.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

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