Which AI Tools are Recommended for Data Science Beginners?

Data, in this modern age, is the new oil. According to Clive Humby, it is of no use when it is unrefined. Analyzing data can reveal many new things about almost anything. It can be related to healthcare, technology, marketing, finance, or any industry. You name it and discover how data analysis is changing the game.

Data science beginners learn how to harness the potential of a vast data set by using specific tools. These days, Artificial Intelligence (AI) has revolutionized the way we see data. Such tools can see the unseen by doing predictive analysis, sentiment analysis, fraud detection, recommendation systems, and decision-making insights.

For beginners, learning how to extract information from data becomes a lot easier with certain AI tools. Let us take a quick look into ten such free AI tools for data science for beginners.

Jupyter Notebook, one of the next-gen free AI tools for data science, allows users to use its web-based interactive development interface for data, code, and notebooks. Users can arrange workflows and do scientific computing on its server.

Features

• Browser-based AI tool for data analysis
• Easy UI for data science features
• Document-centric experience for beginners

Pros

• Ideal for beginners due to its document-centric UI
• Big data tool integrations
• Interactive outputs in HTML, video, image, and custom MIME formats

Cons

• Limited collaboration features
• Debugging tools need more work
• Syncing may take time

Pricing

• It is an open-source platform.

Visit site: Jupyter Notebook

Google Colab comes straight from the house of Google. This Google free AI tools for data science is a perfect example of an AI-driven platform for basic data analysis. Beginners can use this AI tool as it offers excellent computing resources like GPUs, TPUs, etc.

Features

• AI tool for data science, machine learning, and education
• No setup is required from the user end
• Fix bugs and track changes

Pros

• Built-in GitHub integration
• Users can upload data from Google Drive or external storage systems
• Gemini AI API integration

Cons

• Free GPU resource offers limited power and time
• Supports Python only
• Notebook upload is limited to 20 MB size

Pricing

• It has a free version for data science learners.
• Pay As You Go: $11.79/100 Compute Units
• Colab Pro: $11.79/month
• Colab Pro+: $58.99/month
• Colab Enterprise: Custom pricing

Visit site: Google Colab

AutoGluon is a comprehensive AI tool kit for working on data science and deep learning. It is one of the beginner-friendly AI tools for data science that allows quick prototyping without needing expert knowledge. Users can customize its UI features for metrics, processing, and models.

Features

• Build machine learning solutions from scratch
• Pre-built containers and cloud predictors for easy deployment
• Customizable processing, metrics, and modeling features

Pros

• API integration
• AutoGluon community for the vast support
• Software version available for popular operating systems

Cons

• Consumes resources more than other AI tools
• This platform is computationally intensive due to its experimental features

Pricing

• No proper information.

Visit site: AutoGluon

DataRobot is one of the best AI tools for data science for newbie engineers. This AI tool offers the ideal outcomes as per your data set analysis requirements. Users enjoy full visibility and governance over the AI landscape. This tool also evolves with the needs of a user to offer accurate outcomes.

Features

• Use case library for quick deployment
• AI accelerators for accurate outcomes
• Generative and Predictive AI platform

Pros

• No code application builder
• Platform integrations
• AI asset governance

Cons

• Might be complex for beginners
• Manual modeling flexibility is low

Pricing

• It offers a free trial period.
• Essentials: Pricing on request
• Business Critical: Pricing on request

Visit site: DataRobot

Streamlit is one of the top AI tools for data science ideal for learners to use. It is a Python-driven AI tool that can create a shareable web app with provided data scripts. It offers an open-source app framework for data and prediction analysis.

Features

• Open-source library
• Quick building and deployment of data applications
• Custom web app creation for all kinds of industrial data
• Report generation and dashboard view

Pros

• Simple syntax is easy for beginners to learn
• Fast prototyping and web app creation
• Collaboration and interactive visualization features

Cons

• Limited customization capabilities for complex web apps
• Relatively new in the field may lack mature features

Pricing

• Community cloud deployment is free.
• It is an open-source platform.

Visit site: Streamlit

TensorFlow Playground is a neural network platform offering a playground for data science learners. It is one of the top AI tools for data science where users can learn deep learning and neural networks. This open-source platform is available on GitHub with an Apache license for use.

Features

• 6 different kinds of data sets
• Create and run neural networks
• Train and test data ratio customization

Pros

• No code data science operations
• Multiple OS support
• Web app available

Cons

• Lacks computational speed
• Supports only Python

Pricing

• It is an open-source platform.

Visit site: TensorFlow Playground

Kaggle Learn is one of the top AI tools for data science beginners who prefer to use Python and develop data manipulation skills. Users can also elevate their machine learning skills from beginner to intermediate level on this platform. They can visualize data with their coding knowledge.

Features

• No coding experience is needed for data science
• Learn Python and SQL from scratch
• Deep learning introduction
• API integration
• No stress on GPU requirements

Pros

• Keras and TensorFlow integration
• Data cleaning
• AI ethics learning

Cons

• Predictive analysis is not present
• Issues with computational power

Pricing

• It is an open-source platform to learn data science.

Visit site: Kaggle Learn

Vertex AI from Google is one of the best AI tools for data science for beginners. This AI platform offers a fully managed interface for generative AI building and use. It offers an AI studio, an agent builder, and more than 130 foundation models.

Features

• API integration available
• Gemini 1.5-powered AI platform
• Text, image, video, and code prompts
• Its Gemma offers open models

Pros

• 130+ generative AI tools and models
• Integrated AI platform
• ML Ops tools for generative AI and predictive AI

Cons

• Pricier than the other AI tools for data science
• Smaller training sets result in suboptimal model accuracy

Pricing

• It offers a $300-worth free trial for 90 days.
• Image data: $3.465/node hour onwards
• Video data: $3.234/node hour onwards
• Tabular data: $21.252/node hour onwards
• Text data: First 1000 pages free every month and then $1.50/1000 pages onwards
• AutoML: $21.25/hour

Visit site: Vertex AI from Google

Google Cloud is one of the best AI tools for beginners to develop hands-on skills in data science. It is also the top choice for data engineering and ML engineering. Users can use its GPUs and TPUs to compute data and unlock its potential value.

Features

• Complete suite for data management, machine learning, and data analytics
• Data discovery and valuable data source ingestion
• Full governance of data
• Business intelligence and data analysis

Pros

• Train and use ML models
• Responsible AI for data science

Cons

• Complex pricing plans
• Its learning curve is steeper than other AI tools
• SDK API sometimes faces destabilization issues

Pricing

• It offers free credits worth $300 every month.
• Pay As You Go: Custom pricing
• Premium: Custom pricing

Visit site: Google Cloud

H2O AutoML is one of the popular AI tools for data science beginners. This platform leverages a web GUI, R, or Python to train an AI model and save you time. Manual code writing is not mandatory for this tool. You can also enhance the performance of its ML models.

Features

• Set a baseline for scientific applications or research
• ML models can be generated and enhanced
• No manual coding needed

Pros

• Good analytical and prediction AI tool
• No code machine learning platform

Cons

• Model interpretability needs more work
• Users may find difficulty in understanding why a model makes a particular prediction

Pricing

• It is an open-source platform

Visit site: H2O AutoML

After considering these AI tools for data science, Kaggle Learn turns out to be the best platform to learn this subject and develop new skills. The reasons behind choosing this AI tool are:

• Comprehensive learning material for building models for data manipulation.
• Get introduced to Python to learn coding for data science.
• Excel to the intermediate level to learn how to handle missing values, data leakage, non-numeric values, etc.
• Learn to work with databases by using Google BigQuery
• Get introduced to deep learning with Keras and TensorFlow
• Learn how to clean messy data for efficient workflows.

Create an account and register as a user on this open-source platform. Follow the courses and tutorials designed to introduce you to the world of data science.

Even though beginners have simple requirements, they vary. Hence, understand your requirements first regarding an AI tool for data science. It helps you to identify the right tool. Always go with the free trial or version first and then proceed to pay a premium if required. Go for tools like Google Cloud, Vertex AI, or Kaggle Learn to strengthen your data science knowledge.

Do I have to use an AI tool for data science?

AI automates using data sets and assists you in understanding a large volume of data. It offers exclusive insights that are hidden from plain sight. It can assist in interpretive skills, domain expertise, and critical thinking. However, AI is unable to understand specific problems and make ethical decisions.

What are the best AI tools for data science for beginners?

The AI tools for data science ideal for beginners are:

1. Jupyter Notebook
2. Google Colab
3. AutoGluon
4. DataRobot
5. Streamlit
6. TensorFlow Playground
7. Kaggle Learn
8. Vertex AI from Google
9. Google Cloud
10. H2O AutoML

Which open-source AI tools are ideal for data science learners?

Open-source tools like Kaggle Learn, Jupyter Notebook, Streamlit, and TensorFlow Playground are the best open-source AI data science tools for beginners to use.