MODULES INCLUDED

Fundamentals of Machine Learning

  • What is Machine Learning?
  • Process of Machine Learning
  • Life Cycle of Machine Learning
  • Application working in Machine Learning
  • Types Of Machine Learning
  • Setting up the development environment lab

Data Preprocessing

  • Importing Libraries
  • Importing Dataset
  • Taking care of Missing Data
  • Encoding Data: Categorical Data
  • Splitting the dataset into the Training set and Test set
  • Feature Scaling

Supervised Learning Algorithm

  • What is Supervised Learning?
  • Types of Supervised Learning

Regression

  • Simple Linear Regression
  • Multiple Regression
  • Polynomial Regression

Decision Tree

  • Implementation of Decision Tree

Random Forest Regression

  • Implementation of Random Forest Regression

Classification

  • Implementation of Logistic Regression
  • Implementation of Naive Bayes
  • Implementation of Support Vector Machine (SVM)

Clustering

  • K-means Clustering
  • K-means Selecting the Number of Clusters
  • Implementation of k-means clustering
  • Implementation of Hierarchical Clustering
  • Implementation of Apriori

Time Series Modeling

  • Implementation of Time Series Modeling

Reinforcement Learning

  • Implementation of Upper Confidence Bound (UCB)
  • Implementation of Thompson Sampling

Deep Learning and Artificial Neural Network

  • Implementation of Artificial Neural Networks (ANN)
  • Implementation of Convolutional Neural Network (CNN)
  • Implementation of XGBoost

Dimensionality Reduction

  • Implementation of Principal Component Analysis
  • Implementation of Linear Discriminant Analysis
  • Implementation of Kernel PCA

Communication and Perceiving

  • Implementation of Natural Language Processing in Python

Certified Machine Learning Exam

  • There will be an online training followed by a multiple choice exam of 100 marks.
  • 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, then you need to contact us to get assistance for clearing the exam

Certification Benefits

  • Grasp an in-depth understanding of machine learning
  • Understand machine learning with acquired knowledge
  • Have an overview of ML benefits

What you get?

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

CAREER FACTS

Top job functions

  • Marketing
  • E-Commerce
  • Manufacturing
  • Health sector
  • Behavioral science
  • Finance & Investing


What does a Machine Learning Developer do?

A Certified Machine Learning Developer is a skilled professional who understands what machine learning is and how machine learning works. The developer can use this knowledge to build a model from scratch. Students can use this knowledge to research new algorithms. Being a Machine Learning Developer facilitates you to build a model from sample data in order to automate the decision-making process based on data inputs.

The Growth Curve ahead:

After you successfully complete the certification, you can have various opportunities in your professional growth. You can be:

  • Machine learning Developer
  • Machine learning researcher

What are the domains where Machine Learning Developers work?

  • Marketing
  • E-Commerce
  • Manufacturing
  • Health sector
  • Behavioral science
  • Finance & Investing

Final Outcome

After completing this certification, you will be able to master the core concepts of machine learning along with greater understanding of AI and applications.

 

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