Ramesh Banjade

To build an LLM application, start by learning Python and choosing an LLM API such as OpenAI or another model provider. Then build a simple workflow: user input → prompt → LLM → response. For real-world...

If you're starting from scratch, follow this order: Python — Learn programming fundamentals and data handling. SQL — Learn how to work with databases and query data. Machine Learning (ML) —...

AI Engineer vs Data Scientist AI Engineering is often better if you enjoy building AI applications, LLMs, RAG systems, and deploying machine-learning models. Data Science is a better fit if you enjoy...

RAG (Retrieval-Augmented Generation) is an AI technique that lets a language model retrieve relevant information from external data before generating an answer. It helps AI provide more accurate,...

Power BI is a business intelligence and data visualization tool used to turn raw data into clear, interactive reports and dashboards. It helps businesses analyze data, track KPIs, identify trends, and...

Yes — Data Science is still a very good career in 2026, but the field has changed. Companies are collecting more data than ever, while AI is creating even more demand for people who can analyze data,...

Is Data Science a good career in 2026?

To access Google Gemini AI, you can:  Go to the Gemini AI website and create an account Install the Gemini AI client library for your programming language In your code, import the Gemini AI client...

According to Redblink, Google Gemini scored 90% when tested on a range of topics, including math, physics, and law. This is higher than ChatGPT's 86.4%. Gemini also outperformed ChatGPT in text and reasoning,...

Google Gemini is a set of large language models (LLMs) that will power many Google products and services. Read the blog for details: Introducing Gemini: our largest and most capable AI model https://blog.google/technology/ai/google-gemini-ai/

There is a popular method known as elbow method which is used to determine the optimal value of K to perform the K-Means Clustering Algorithm. The basic idea behind this method is that it plots the various...

Univariate statistics summarize only one variable at a time. Bivariate statistics compare two variables. Multivariate statistics compare more than two variables. Univariate, Bivariate and Multivariate...

The main difference between supervised and unsupervised learning is the need for labeled training data. Supervised learning Uses labeled input and output data. The algorithm learns from the training...

Python is a programming language widely used by Data Scientists. Python has in-built mathematical libraries and functions, making it easier to calculate mathematical problems and to perform data analysis....

The hardest parts of data science What the Hardest Thing About Data Science Hard Problems in Data Science: Causality, Sequential Learning and Complex Dynamic Theories The Hardest Part of Data Science?

SQL is a standard database language used to communicate with databases. It is widely used for managing and manipulating data in relational databases. It is a powerful tool for data scientists, it allows ...

Data science interviews can be difficult because they require candidates to demonstrate a variety of skills. These skills include: Technical skills (Programming Skills) Problem-solving Communication...

Every month  Microsoft  update the new feature in power BI. Some of the updated features of this month are DAX Query view, Semantic Model Scale-out, and Advanced Filtering for Paginated Reports. Follow...