2024 - AI (Artificial Intelligence) Roadmap in Telugu | Vamsi Bhavani

2024 - AI (Artificial Intelligence) Roadmap in Telugu | Vamsi Bhavani

Welcome back to Vamsi Bhavani. In this article, we will discuss how to start learning AI in 2024 and how you can proceed easily if you have a plan of action.

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First of all, you need to get a programming language, and in my opinion, Python is the best language. Start by learning Python programming language. For those who are comfortable with Telugu, the 30 Days Challenge from Vamsi Bhavani will definitely help you very much.

Step 1: Learn Python

You need to:

1. Learn Python from Vamsi Bhavani.
2. Know some mathematics crucial for machine learning because often, you deal with benchmark models that require mathematical understanding to comprehend.
3. Follow videos by Andrew Ng on YouTube. His videos are excellent and he is a renowned instructor in the Machine Learning and Data Science field.

Step 2: Familiarize with Basic Tools

Learn some basic tools in Python, such as NumPy and Matplotlib. Use GitHub repositories and YouTube videos to learn:

1. NumPy
2. Matplotlib

Step 3: Understand Notebooks

• Learn about Jupyter Notebooks and Google Colab as they are essential for data training and model implementation.

Structured Curriculum

Explore structured curriculums like Data Science Boot Camp from various schools which offer:

1. Project-based learning
2. Unlimited job opportunities
3. Live instructor-led sessions
4. Comprehensive training on tools and frameworks like TensorFlow, PyTorch, Hugging Face, Gradio, etc.

Step 4: Learn Basic Algorithms

Understand basic algorithms in machine learning, such as:

1. Regression
2. SVMs
3. Decision Trees

Step 5: Implement with SciKit Learn

Learn about SciKit Learn, a widely-used library for implementing machine learning models. It allows you to:

1. Implement all major algorithms easily.
2. Train and predict models by calling pre-implemented methods.

Step 6: Move to Deep Learning

Learn the basics of deep learning, and understand the difference between:

1. Machine Learning
2. Deep Learning
3. Supervised Learning
4. Unsupervised Learning
5. Reinforced Learning

Step 7: Utilize Advanced Frameworks

Familiarize yourself with advanced frameworks like TensorFlow and PyTorch, which will help in training deep learning models.

Step 8: Explore Use Cases

Look into various use cases such as:

1. Facial recognition
2. Image classification
3. Voice cloning
4. Deep fakes

Use open-source contributions on GitHub to:

1. Understand code implementation
2. Learn model architecture and training methods

Final Steps: Practice and Specialize

• Make use of datasets from platforms like Kaggle to practice data cleaning and model training.
• Specialize in a domain that excites you.

Remember, it will take time – roughly six to seven months – so be patient and consistent with your learning.

If this article helps, please hit the like, share, and subscribe button. Jai Hind, Jai Bharat.

Keywords

• AI (Artificial Intelligence)
• Python Programming
• Machine Learning
• Deep Learning
• Data Science
• Andrew Ng
• NumPy
• Matplotlib
• Jupyter Notebooks
• Google Colab
• SciKit Learn
• TensorFlow
• PyTorch
• Kaggle

FAQ

Q1: What programming language is recommended for starting AI in 2024?

A: Python is highly recommended for starting AI due to its simplicity and extensive libraries.

Q2: Where can I learn Python in Telugu?

A: You can follow the 30 Days Challenge from Vamsi Bhavani to learn Python in Telugu.

Q3: Is mathematics important for learning machine learning?

A: Yes, understanding the mathematics behind machine learning models is crucial for gaining a deep comprehension of how these models work.

Q4: Which online resources are good for learning machine learning?

A: Videos by Andrew Ng on YouTube are highly recommended. They provide a thorough understanding of machine learning basics and advanced topics.

Q5: What are some basic tools I should learn in Python?

A: You should learn NumPy and Matplotlib as they are essential for data manipulation and visualization.

Q6: What are Jupyter Notebooks and Google Colab?

A: They are interactive notebooks that facilitate code implementation, data visualization, and model training in a user-friendly environment.

Q7: What are some key machine learning algorithms I should know?

A: Key algorithms include Regression, SVMs, and Decision Trees.

Q8: What is SciKit Learn?

A: SciKit Learn is a Python library that simplifies the implementation of machine learning algorithms and models.

Q9: What is the difference between machine learning and deep learning?

A: Machine learning focuses on algorithms that learn from data, while deep learning involves neural networks with multiple layers that perform more complex data-processing tasks.

Q10: How long will it take to learn AI and machine learning?

A: It typically takes around six to seven months to learn the basics and gain proficiency, so be patient and consistent with your learning process.