Learning Objectives

Beginner-friendly Artificial Intelligence course

Packing all the information that I needed while applying AI for more than a decade and converting that to a guided journey through AI, from learning Python, core concepts, ML notions, object detection, GenAI and deployment. Oh, how I would have loved to have this opportunity while progressing through my job.

Foundational Modules

Discover the Basis of AI

Module 1: Foundations of AI and Machine Learning

By the end of this module, you will be able to understand AI concepts like Machine Learning, Artificial Intelligence, GenAI, LLM, DeepLearning and to identify the differences between supervised, unsupervised, and reinforcement learning, and explain AI’s real-world uses.
Module 2: Data Handling and Preprocessing

By the end of this module, you will be able to clean and preprocess a raw dataset, handle missing data, and engineer features for machine learning models.
Module 3: Supervised Learning and Model Building

By the end of this module, you will be able to build, train, and evaluate a supervised learning model (e.g., decision tree or SVM) using real-world data.
Module 4: Model Evaluation, Tuning, and Optimization

By the end of this module, you will be able to evaluate a model’s performance using key metrics (accuracy, precision, recall) and improve the model through hyperparameter tuning.
Module 5: Unsupervised Learning

By the end of this module, you will be able to implement unsupervised learning techniques, such as K-means clustering and PCA, to discover patterns in unlabeled data.
Module 6: Deep Learning and Neural Networks

By the end of this module, you will be able to construct and train a basic neural network model using a deep learning framework like Tensorflow

AI Components

AI Components to Discover

Module 7 : Object detection

By the end of this module, you will know how to do data labeling and train a model to detect standard and custom objects.
Module 8: Natural Language Processing (NLP)

By the end of this module, you will be able to understand NLP concepts, preprocess text data, apply NLP techniques (e.g., tokenization and sentiment analysis), and implement basic NLP models in Python.

GenAI

Discover GenAI World

Module 9: Generative AI and GPT Models

By the end of this module, you will be able to understand GenAI concepts, explore different GenAI models and services and generate text, images, audio and videos using existing Generative AI models.

Getting to production

How to get to production?

Module 10: AI Model Deployment and Integration

By the end of this module, you will be able to deploy a machine learning model in a cloud environment (e.g., AWS, Google Cloud) and integrate it into an application or expose it through a Python API.
Module 11: AI Ethics, Explainability, and Capstone Project

By the end of this module, you will be able to apply ethical principles in AI, explain your model’s decisions using SHAP or LIME, and complete a real-world AI capstone project.

Step into the Future

Your Future Starts Today

Master the skills to excel in Artificial Intelligence with our beginner-friendly course, designed for software developers ready to elevate their careers. Learn everything from data handling to advanced AI deployment in bite-sized, weekly modules. Enroll now and join the community that's shaping tomorrow!

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