MODULES INCLUDED

Overview

  • Introduction

Machine Learning Models & Datasets

Models and their compatibility with the Dataset

Performance of ML Models

  • Confusion matrix
  • Accuracy, Precision, Recall & F1-score
  • AUC-ROC curve
  • LOG-LOSS Function

 

Improving Performance of ML Models

  • Cross-Validation
  • Hyperparameter Tuning
  • Dimensionality Reduction
  • Feature selection using the wrapper method
  • Feature selection using the filter method
  • Feature selection using the embedded method
  • Feature extraction
  • Feature extraction: PCA
  • Feature extraction: LDA
  • Ensemble Modeling: Bagging
  • Ensemble Modeling: Boosting

Deep Learning

  • Introduction to Deep Learning
  • Introduction to optimization
  • Gradient Descent
  • Activation function
  • Neural Networking
  • Keras
  • Tensorflow
  • Computer Vision
  • Backtracking

Artificial Intelligence

  • Introduction to artificial intelligence 
  • NLP

Limitation of Artificial Intelligence

  • Setbacks of Artificial Intelligence

Certified Advanced ML Develper™-Exam

  • A multiple-choice exam of 100 marks will follow online training.
  • You need to acquire 60+ marks to clear the exam.
  • If you fail, you can retake the exam after one day.
  • You can take the exam no more than 3 times.
  • If you fail to acquire 60+ marks even after three attempts, you need to contact us to get assistance in clearing the exam.

RECOMMENDED LEARNING METHODOLOGY

  • Recommend allocating 1 hour daily in order to complete the course in a span of 8 days.
  • Though you can attempt the online exam anytime as per your convenience, we highly recommend attempting the exam within 9 days of course completion, as the subject will be fresh in your mind and you get sufficient time to prepare/revise as well.

CERTIFICATION BENEFITS

  • Grasp an in-depth understanding of Machine Learning.
  • Have a detailed overview of the different techniques used in Machine Learning.
  • Have an overview of the various Models and Datasets in Machine Learning.

WHAT DO YOU GET?

  • Global Tech Council Certification
  • Lifetime access to the course content
  • 24*7 Support for all your queries

CAREER FACTS

Top job functions

  • Cyber Security Professional
  • Software Developers
  • Database Administrators
  • IT Security Engineers
  • Others

Machine learning is a subsection of artificial intelligence. ML aims to create algorithms and systems that can evaluate processes and learn from data.  The growth of machine learning and the use of deep learning is trending these days. However, machine learning is impossible without data. ML algorithms need to be fed with accurate and labeled data. Machine learning is undeniably beneficial to everyone.

What does a Certified Advanced ML Developer do?

 

A Machine Learning Developer’s responsibilities will vary depending on the industry, organization, and team with whom they work. While the core task in the industry is to design, implement, and maintain machine learning systems using data science and computer science fundamentals, this can take many different forms depending on the type of project given.

 

The Growth Curve ahead

 

Upon completing of this certification, you will have multiple opportunities in various fields related to machine learning. You can be:

 

  • AI / MI Developer
  • Data Scientist
  • Human-centered AI systems designer
  • Robotics Engineer

 

What are the domains where ML Developers work?

 

  • Supply-chain management: ML developers can work in the supply-chain industry. They assist in managing the supply network efficiently.
    Machine learning algorithms provide insights on how supply chain performance can be enhanced and helps in determining and forecasting the growth of the company.
  • Financial Sector: ML developers can be employed in the financial sector to detect frauds, automate trading activities and provide financial advisory services to investors. In finance, ML can help improve efficiencies and serve clients with better offers and services.
  • Healthcare Industry: Machine learning is also used in the healthcare sector. It helps manage and store medical records and data; it also helps in medical diagnosis and detecting illness at an early stage. The scope of machine learning in the medical field is increasing as advanced technology is updated now and then.
  • Automotive Industry: Machine learning is developing and impacting the automotive industry. ML enables the automotive industry to improve manufacturing, increase the supply chain, and make the driving experience safer and more comfortable.

Final Outcome

After completing this certification, you will be able to master the advanced concepts of machine learning along with a better understanding of models and datasets, deep learning, and also artificial learning. 

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