Certified Artificial Intelligence Developer Program

Embark on a transformative journey into the world of Artificial Intelligence with the Certified Artificial Intelligence Developer program. This comprehensive course is designed to meet the dynamic needs of the industry, providing you with the skills and knowledge to excel as an AI Developer.

Course Overview:

Our AI Developer Certification program takes you from the fundamentals of AI to the intricacies of creating, training, and optimizing AI models on both labeled and unlabeled datasets. Whether you’re a beginner or an experienced professional, this course offers a self-paced learning journey that blends cutting-edge knowledge with practical application.

Additionally, our course includes practical hands-on exercises and lab sessions, ensuring you can effectively grasp and implement the concepts in solving real-life problems. These skills will help you ace machine learning interview questions and land your dream job.

Join this program and be at the forefront of innovation in the ever-evolving field of Artificial Intelligence. Elevate your career with the skills demanded by today’s tech landscape.

Key outcomes of the course include Developing image recognition systems and computer vision applications, Creating your own recommendation engine.

Beginner to Intermediate Learners: Those new to the field of AI, machine learning, and data science will gain a solid foundation and build up to advanced concepts.
Professional Developers: Software engineers looking to expand their skill set to include AI and machine learning, enabling them to create intelligent applications and solutions.
Data Analysts: Those working with data who want to learn how to leverage AI to derive deeper insights and create predictive models.
Business Leaders and Executives: Professionals seeking to understand the strategic implications of AI and how to leverage it to gain a competitive edge in their industry.
University Students: Undergraduates or postgraduates in computer science, engineering, or related fields looking to complement their academic knowledge with practical AI skills.
Startup Founders: Entrepreneurs looking to build AI-driven products or startups and need a comprehensive understanding of how to develop and implement AI technologies.

Course Content

AI: Big Data and AI

Introduction to Big Data and AI

06:37
Data Processing and Analytics

05:00
Advanced Analytics and AI Techniques

04:21
Applications and Case Studies

04:31
Hands-on Exercise Data Pre-processing

14:16

AI: Artificial Intelligence on the Cloud

AI: AI in Banking

AI: Exploring Feature Selection

AI: Chatbots

AI: White Box XAI for AI Bias & Ethics

Essential ML: Machine Learning and Python

Essential ML: Supervised Learning – Classification and Regression

Essential ML: Unsupervised Learning – Detecting Patterns

Essential ML: Dimensionality Reduction

Essential ML: Visualising Data and Machine Learning

NLP: Natural Language Processing Using Python

NLP: Transform Text File into Data Structure

NLP: Word Embedding and Text Distance Metrics

NLP: Document, Sentence and Character Level Embeddings

NLP: Text Data Analysis

A course by

Pushkal Shukla

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Certified Artificial Intelligence Developer Program

Course Overview:

What Will You Learn?

Requirements

Audience

Course Content

AI: Big Data and AI

Introduction to Big Data and AI

Data Processing and Analytics

Advanced Analytics and AI Techniques

Applications and Case Studies

Hands-on Exercise Data Pre-processing

AI: Artificial Intelligence on the Cloud

Introduction to Cloud Computing and AI

Hands-on Exercise on pandas data frame

AI Services on Cloud Platforms

Hands-on Exercise NLP on cloud

Big Data and AI Integration on the Cloud

Hands-on Exercise Exploratory data analysis

Advanced Topics and Future Trends

AI: AI in Banking

Introduction to AI in Banking

AI Applications in Banking Operations

AI for Customer Experience Enhancement

Future Trends and Ethical Considerations

AI: Exploring Feature Selection

Introduction to Feature Selection

Filter Methods

Hands-on Exercise Information Gain Classification and Regression

Wrapper Methods

Embedded Methods and Advanced Techniques

Hands-on Exercise Feature Selection Techniques

AI: Chatbots

Introduction to Chatbots

Building AI-based Chatbots

Advanced Chatbot Techniques

Ethical Considerations and Future Trends

AI: White Box XAI for AI Bias & Ethics

Introduction to AI Bias and Ethics

Interpretability and Explainability in AI

Fairness in AI

Case Studies and Best Practices

Essential ML: Machine Learning and Python

Introduction to Python for Machine Learning

Hands-on Exercise Introduction to Python

Introduction to NumPy and Pandas

Hands-on Exercise Python working with Pandas and NumPy

Introduction to Machine Learning with Scikit-Learn

Model Deployment and Real-world Applications

Essential ML: Supervised Learning – Classification and Regression

Introduction to Supervised Learning and Linear Regression

Hands-on Exercise Linear Regression

Classification Algorithms

Hands-on Exercise Classification Algorithms Part-1

Advanced Classification Techniques

Essential ML: Unsupervised Learning – Detecting Patterns

Introduction to Unsupervised Learning and Clustering

Hands-on Exercise Clustering Algorithms

Density-based Clustering and Dimensionality Reduction

Hands-on Exercise DBSCAN

Association Rule Mining and Anomaly Detection

Hands-on Exercise Apriori Algorithm

Advanced Topics and Real-world Applications

Essential ML: Dimensionality Reduction

Introduction to Dimensionality Reduction and Principal Component Analysis (PCA)

Hands-on Exercise Dimensionality Reduction PCA

Linear Dimensionality Reduction Techniques

Hands-on Exercise Linear Dimensionality Reduction Algorithms

Non-linear Dimensionality Reduction Techniques

Hands-on Exercise Non-linear Dimensionality Reduction Algorithms

Advanced Topics and Applications

Hands-on Exercise Autoencoders

Essential ML: Visualising Data and Machine Learning

Introduction to Data Visualisation and Basic Plotting

Hands-on Exercise Data Visualisation

Advanced Plotting Techniques

Dimensionality Reduction Techniques for Visualisation

Hands-on Exercise Visualising Dimensionality Reduction Techniques

Interactive Dashboards and Real-world Applications

NLP: Natural Language Processing Using Python