MODULES INCLUDED

  • What is AI?
  • The History of AI
  • Different Types of AI
  • AI vs. Machine Learning vs. Deep Learning
  • Python Basics
  • Installing python
  • Python Data Structures
  • Control Flow in Python
  • Functions in Python
  • Modules and Packages
  • Introduction to NumPy
  • Introduction to Pandas
  • Introduction to Matplotlib
  • Understanding Machine Learning
  • Regression
  • Classification
  • Clustering
  • Dimensionality Reduction
  • Overfitting, Underfitting, and Model Selection
  • Introduction to Neural Networks
  • Types of Neural Networks
  • Neural Network Components
  • Activation Functions and Cost Functions
  • Backpropagation and Gradient Descent
  • Regularization Techniques (Dropout, Batch Normalization)
  • Convolutional Neural Networks for Image Processing – Part 1
  • Convolutional Neural Networks for Image Processing- Part 2
  • Recurrent Neural Networks for Sequence Data
  • Generative Adversarial Networks
  • Transfer Learning and Fine-tuning
  • Natural Language Processing
  • Computer Vision
  • Speech Recognition and Synthesis (part 1)
  • Speech Recognition and Synthesis (part 2)
  • AI in Healthcare
  • AI in Business and E-commerce
  • AI in Autonomous Vehicles
  • AI in Entertainment
  • AI in Finance
  • AI in Blockchain
  • AI in IOT
  • Understanding AI Ethics
  • Potential Pitfalls and
  • Controversies in AI
  • Strategies for Responsible AI Deployment
  • Tensorflow
  • PyTorch 2.0
  • Cloud AI Services (AWS, Google Cloud AI, Azure AI)
  • Regression using python
  • Classification using python
  • Clustering using python
  • There will be 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

  • Overview of AI and its applications: The certification program provides an overview of AI and its various applications, giving individuals a comprehensive understanding of the field.
  • Insights of AI technologies and tools: The certification program covers a range of AI technologies and tools, including natural language processing, computer vision, and machine learning algorithms, enabling individuals to gain insights into these technologies.
  • A deep understanding of the fundamentals of machine learning and deep learning: The certification program provides a deep understanding of the fundamentals of machine learning and deep learning, which are critical skills for AI experts.
  • An opportunity to prove your knowledge and skills in the AI space: The certification program provides individuals with an opportunity to demonstrate their knowledge and skills in the AI space, making them more attractive to employers.
  • Career advancement: Certified AI experts have a competitive advantage in the job market, with the potential for higher salaries and more significant job opportunities

What you get?

  • Global Tech Council Certification.
  • Lifetime validity of the certification.
  • 24*7 Support for all your queries.
  • Hands-on industry project experience.

CAREER FACTS

Top job functions

  • AI/ML Engineer​
  • AI/ML Solutions Architect​
  • Data Scientist​
  • AI/ML Data Analyst​
  • AI/ML Researcher​


What is the role of an AI developer?

A Certified AI Developer is a trained professional who understands the fundamentals of Artificial Intelligence and possesses the necessary skills and knowledge to design, develop, and implement artificial intelligence solutions that can automate processes and improve decision-making.

The Growth Curve Ahead:

  • SaaS Industry
  • Education and training industry
  • E-commerce industry
  • Social network, media, and communications industry

Final Outcome

After completing this certification, you would have mastered the core concepts of Artificial Intelligence.

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Success Stories