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Frequently Asked Questions

AI is a technology that enables computers to mimic human intelligence and perform more complex and time-consuming tasks in a faster and more efficient way. AI systems learn and improve by analyzing large amounts of data and finding correlations and patterns in it.

Some applications of AI.

E-commerce: AI-powered recommendation systems enables personalized user experiences, depending on their history.
Conversational Chatbots – These AI Models generate human like text responses. It makes them suitable for tasks like answering questions, providing explanations, and engaging in dialogues.
Social Media – AI in social media can curate personalized news feeds and content aligning with user interests.

Machine Learning is a subset of AI that enables systems to learn from data and make decisions without explicit programming. It focuses on developing algorithms and statistical models. The four types of Machine Learning are Supervised ML, Unsupervised ML, Semi-supervised ML, Reinforcement Learning

Application of Machine Learning

Predictive Analytics – ML is used to forecast trends in businesses and Finance
Sentiment Analysis – Identifying and categorizing customer sentiment as positive, negative, or neutral.

Machine Learning, a tool from Rubiscape's end-to-end platform, allows you to build models quickly and effortlessly. Its no-code, low-code interface simplifies the process, even with limited coding experience.

A Data Scientist builds predictive models using advanced analytics and machine learning, primarily with Python and R. A Data Analyst interprets and visualizes data for insights, using SQL and tools like Tableau and Excel. A Data Engineer designs and maintains data infrastructure, focusing on ETL processes and database management, using SQL, Python, and tools like Hadoop and Spark.

Rubiversity equips you with the skills needed for various Data Science roles through specialized courses and hands-on projects. Our curriculum is designed to meet the latest industry demands, ensuring you gain relevant, practical experience.

In Data Science, popular programming languages include Python for its simplicity and vast libraries, R for statistical analysis and visualization, and SQL for querying relational databases. Essential libraries include NumPy and Pandas for data manipulation, Matplotlib and Seaborn for visualizations, and Scikit-Learn, TensorFlow, and PyTorch for developing machine learning and deep learning models.

Rubiscape, an end-to-end Data Science platform, supports your learning by offering a comprehensive toolset. With tools like Connect for integrating data from over 20 sources, Metadata Manager for creating data dictionaries, Data Integrator for building pipelines, Dashboard Designer for interactive dashboards, and Machine Learning for model development and deployment, Rubiscape facilitates a streamlined and effective data science process.

Gen AI or Generative AI, is an branch of Artificial Intelligence that focuses on creating new content. The content can be text, images, video, audio, or even code. Unlike traditional AI, which is designed to recognize patterns and make predictions based on existing data, generative AI models create new data that mimics the original data's characteristics.

A few examples of GAN’s include:

GPT - Generative Pre-trained Transformer models, used for text generation
GAN - Generative Adversarial Networks, which are used to create realistic images

With Rubiscape, you can experiment with generative AI models, allowing you to develop innovative solutions across various domains.

Elevate Your Skills with Gen AI Fundamentals

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Advance Course in

Artificial Intelligence and Machine Learning

1 YearDuration

44 Credit Points

Elevate Your Skills with
Gen AI Fundamentals

Visual
Designer

Data
Analyst

Business
User

Data
Analyst

Business
Analyst

Data
Scientist

Visual
Designer

Data
Analyst

Business
User

Artificial Intelligence and
Machine Learning

1 Year
Duration

44
Credit Points

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