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Zero to Master Program

Artificial Intelligence(AI)

Artificial Intelligence (AI) is a field of computer science that focuses on creating systems capable of performing tasks that typically require human intelligence. These tasks include problem-solving, learning, planning, language understanding, and perception. AI programs can be categorized into narrow AI, which is designed for specific tasks, and general AI, which aims for broader, human-like cognitive abilities. Key techniques in AI include machine learning, where systems learn from data, and deep learning, a subset of machine learning involving neural networks. AI applications span various domains, such as healthcare, finance, autonomous vehicles, and robotics. Ethical considerations and the impact on jobs and society are critical discussions in AI development. The field is rapidly evolving, with ongoing research pushing the boundaries of what machines can achieve.

Fee

COURSE FEE

30,000

4.8

12K+ Learners enrolled

100 +

Duration(Hours)

350+

Problems

This is where you embark on an amazing journey!

Most flexible program in the industry

Freedom to learn

Watch classes any time at your convenience

Cheat days

Catch up on the course when life is calling you elsewhere

Features that keep you going

A structured curriculum that makes learning easy

Practice code problems of varying difficulty

Engagement coach to keep you motivated

Compile & run in an integrated coding environment

Get doubts resolved in 30 mins

1:1 sessions over voice call & chat with our skilled teaching assistants

Industry leading mentors to help you grow

1:1 Mock interviews with resume and career guidance

Structured feedback to make you better

Get a chance to be referred to your mentors’ company

Experience a seamless job switch with hiring assistance

Skill-based hiring across all levels of experience

The results

110%

Average salary hike

7000+

Transitions to product companies

250+

Trusted placement partners

Frequently asked but seldom read questions

Yes, this course is entirely offline, and we offer some courses online as well.

None! Whether you’re completely new to the job field or have had some exposure, Algoxfusion Certificate is the right program for you..

You can find the ‘Get Certified’ option at the end of the Lessons in the table of contents. it will be shown only after completing all the lessons with 100% progress.

Submissions are evaluated based on criteria such as correctness, completeness, critical thinking, and adherence to instructions, typically using rubrics or grading guidelines provided by the instructor.
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Meet the faculty legends that will make you legendary

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Praveen Kumar

Founder & Instructor

Praveen has a full stack development experience and professional instructor and trainer for Flutter, Data Science, Machine Learning and Python Programming. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming, the ability to analyze data, and the skills needed to present the data in clear and beautiful visualizations.

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Lenin Prakash

Co-Founder & Instructor

He is an expert in JavaScript & React (Front-end) and has worked on open-source projects like Firebug and Zulip. He has also served as a GCI (Google Code-In) Mentor with Zulip. In his previous role as a Software Engineer he has worked for Goibibo-MMT.

Course curriculum for the curious

  • -Definition and History of AI
  • -Types of AI: Narrow AI, General AI, and Superintelligent AI
  • -Applications of AI in various industries
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  • -Search Algorithms
  • -Optimization
  • -Game Playing:
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  • -Introduction to Machine Learning
  • -Supervised vs. Unsupervised Learning
  • -Classification Algorithms: Decision Trees, K-Nearest Neighbors, Naive Bayes
  • -Regression Algorithms: Linear Regression, Logistic Regression
  • -Evaluation Metrics: Accuracy, Precision, Recall, F1 Score
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  • -Introduction to neural networks
  • -Perceptrons and Multilayer Perceptrons
  • -Backpropagation Algorithm
  • -Introduction to Deep Learning
  • -Convolutional Neural Networks (CNNs)
  • -Recurrent Neural Networks (RNNs)
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  • -Basics of NLP
  • -Text Processing: Tokenization, Lemmatization, Stop Words
  • -Sentiment Analysis
  • -Machine Translation
  • -Chatbots and Conversational AI
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  • -Introduction to Robotics
  • -Robot Kinematics and Dynamics
  • -Sensors and Actuators
  • -Path Planning and Navigation
  • -Robotics in AI
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  • -Ethical Considerations in AI
  • -Bias and Fairness in AI
  • -AI and Privacy
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