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This program offers a structured learning path covering essential AI concepts, advanced techniques, and practical applications, preparing participants to tackle real-world challenges effectively.

Prerequisites

  • Programming Proficiency: Strong foundation in Python programming.
  • Mathematical Foundations: Understanding of mathematics, statistics, and optimization relevant to AI.
  • Data Processing Skills: Experience with data processing and exploratory analysis.
  • Basic AI Knowledge: Familiarity with machine learning and deep learning concepts.

 

Course Modules and Curriculum

Course Introduction Watch Demo
  • 1.1 Introduction to AI Watch Demo
  • 1.2 Types of Artificial Intelligence Watch Demo
  • 1.3 Branches of Artificial Intelligence
  • 1.4 Applications and Business Use Cases
  • 2.1 Linear Algebra Watch Demo
  • 2.2 Calculus Watch Demo
  • 2.3 Probability and Statistics Watch Demo
  • 2.4 Discrete Mathematics
  • 3.1 Python Fundamentals Watch Demo
  • 3.2 Python Libraries
  • 4.1 Introduction to Machine Learning
  • 4.2 Supervised Machine Learning Algorithms
  • 4.3 Unsupervised Machine Learning Algorithms
  • 4.4 Model Evaluation and Selection
  • 5.1 Neural Networks
  • 5.2 Convolutional Neural Networks (CNNs)
  • 5.3 Recurrent Neural Networks (RNNs)
  • 6.1 Image Processing Basics
  • 6.2 Object Detection
  • 6.3 Image Segmentation
  • 6.4 Generative Adversarial Networks (GANs)
  • 7.1 Text Preprocessing and Representation
  • 7.2 Text Classification
  • 7.3 Named Entity Recognition (NER)
  • 7.4 Question Answering (QA)
  • 8.1 Introduction to Reinforcement Learning
  • 8.2 Q-Learning and Deep Q-Networks (DQNs)
  • 8.3 Policy Gradient Methods
  • 9.1 Cloud Computing for AI
  • 9.2 Cloud-Based Machine Learning Services
  • 10.1 Understanding LLMs
  • 10.2 Text Generation and Translation
  • 10.3 Question Answering and Knowledge Extraction
  • 11.1 Neuro-Symbolic AI
  • 11.2 Explainable AI (XAI)
  • 11.3 Federated Learning
  • 11.4 Meta-Learning and Few-Shot Learning
  • 12.1 Case Study 1: Communicating AI Projects
  • 12.2 Case Study 2: Documenting AI Systems
  • 12.3 Case Study 3: Ethical Considerations

Tools

GitHub Copilot

GitHub Copilot

Lobe

Lobe

H2Oai

H2Oai

Snorkel

Snorkel

Who Should Enroll?

This certification is ideal for:

  • Software Developers & Engineers
    - Learn how to integrate AI into software applications.
  • Data Scientists & AI Enthusiasts
    - Gain expertise in AI model training and deployment.
  • IT & Cloud Computing Professionals
    - Understand how AI can be leveraged in cloud environments.
  • AI & ML Researchers
    - Strengthen your knowledge in AI frameworks and deep learning techniques.
Key Learning Outcomes
  • Develop AI models and applications using industry-leading tools.
  • Gain expertise in deep learning, natural language processing, and computer vision.
  • Learn how to train, optimize, and deploy AI models in production environments.
  • Explore ethical AI principles, fairness, and bias mitigation in AI development.

Enroll Now

Take the first step towards becoming an AI expert.
Enroll in our AI+ Developer™ Course today and unlock the potential of coding to drive your career forward.

Exam Objectives

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Proficiency in Python for AI

Develop a strong foundation in Python programming, a key skill for implementing AI algorithms, data processing, and building AI applications efficiently.

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Mastering Deep Learning Techniques

Gain expertise in machine learning and deep learning methodologies to solve challenges in classification, regression, image recognition, and natural language processing.

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Cloud-Based AI Development

Acquire hands-on experience in deploying AI applications using AWS, Azure, and Google Cloud, ensuring scalability and efficiency in AI-driven solutions.

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AI Project Management Skills

Learn to effectively manage AI projects, covering aspects such as planning, resource allocation, risk management, and stakeholder communication from initiation to completion.

Career Opportunities Post-Certification

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Median Salaries

$77,311

AI Salary Icon

With AI Skills

$125,439

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% Difference

Product Manager

AI Developer

Design and implement AI solutions across various industries.

Data Analyst

Machine Learning Engineer

Build and optimize machine learning models for practical applications.

AI Architect

Data Scientist

Analyze complex data sets to derive actionable insights using AI techniques.

ML Engineer

Research Scientist

Conduct research to advance AI methodologies and applications.

Join AI Course & Become Future-Ready!

Stay ahead in the AI-driven world. Enroll now to gain in-demand skills, hands-on experience, and industry-recognized certification for a future-ready career.

Get Certified | Check Matching Certification To Your Career

Frequently Asked Questions

This certification is ideal for individuals with a foundational understanding of programming and AI concepts who wish to advance their skills in AI development.

Participants will acquire hands-on experience in Python programming, data processing, deep learning, and can specialize in areas such as NLP, computer vision, or reinforcement learning.

Earning the AI+ Developer™ Certification demonstrates your expertise in AI development, enhancing your professional profile and opening opportunities in various tech-driven industries.

A solid foundation in Python programming, mathematics, and basic AI concepts is recommended to maximize the learning experience.

The certification exam consists of 50 multiple-choice questions to be completed in 90 minutes, with a passing score of 70% required to earn the certification.