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Adventures in Artificial Intelligence

Join us in the "Adventures in Artificial Intelligence" course and unlock the power of smart machines, discovering the possibilities that AI holds for the future!

20 live classes.

Self Study Material

Self Study Material

There will be a minimum of 20 classes for this course --a minimum of one hour each and minimum 20 days.

Self Study Material

Self Study Material

Self Study Material

Keynotes and Videos will be provided for self study. These are well designed keynotes. 

Live Lectures

Self Study Material

Live Lectures

Students will able to interact with the teacher and can ask questions anytime.

Syllabus

  • Define artificial intelligence and its applications.
  • Explore real-world examples of AI in everyday life.
  • Discuss the benefits and potential risks of AI.

  • Understand the importance of data in AI.
  • Introduce basic concepts of data collection, cleaning, and preprocessing.
  • Learn about algorithms and how they help machines make decisions.
  • Explore different types of algorithms used in AI, such as supervised learning, unsupervised learning, and reinforcement learning.

  • Introduce the concept of machine learning and its subfields.
  • Explore supervised learning: classification and regression.
  • Teach unsupervised learning: clustering and dimensionality reduction.
  • Explain reinforcement learning and its application in creating AI agents.
  • Discuss the ethics of AI and biases in machine learning algorithms.

  • Introduce neural networks as the foundation of deep learning.
  • Explain the structure and components of neural networks.
  • Teach basic concepts of forward and backpropagation.
  • Explore popular deep learning architectures like convolutional neural networks (CNNs) and recurrent neural networks (RNNs).
  • Engage students in creating and training their own simple neural network models using user-friendly platforms or libraries.

  • Introduce the field of natural language processing (NLP) and its applications.
  • Teach basic techniques in NLP, such as tokenization, stemming, and sentiment analysis.
  • Explore language modeling and text generation using recurrent neural networks.
  • Discuss the challenges and ethical considerations in NLP, including bias and privacy concerns.

  • Explore practical applications of AI in various fields like healthcare, transportation, and entertainment.
  • Engage students in project-based learning, where they design and implement their AI systems or applications.
  • Encourage creativity and critical thinking by allowing students to address real-world problems using AI techniques.

Why We Started Teaching ?

We started teaching as an experimental service during Covid-2020. 

We have received great reviews and more are inquiring for courses. 


We have seen people are giving more than $1000 for coding courses which we think is too expensive and education should be affordable because it is the fundamental to development and growth. Many are learning from YouTube, and various other places. There’s nothing bad in that but the way is pathless and it is easier to deviate.


Everyone has their own background of knowledge and one thing which they choose themselves is path. They navigate from one video to another and most find themselves nowhere. Mentorship is necessary to achieve your goals in the shortest time and I think it’s also productive.


We offer online classes which is live and student can interact with the mentor unlike pre-recorded videos. Our courses are project based not slide based. 

We teach industry-based code not class code. 

Want to learn with us!!

We will reach you with more details about the course.

Learn coding by building projects.

Find out more

For more info

Please, reach here if you want to join this course!!

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