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10 Must-Have AI Engineering Skills in 2024

Data Science Dojo

From healthcare where AI assists in diagnosis and treatment plans, to finance where it is used to predict market trends and manage risks, the influence of AI is pervasive and growing. As AI technologies evolve, they create new job roles and demand new skills, particularly in the field of AI engineering.

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Data Scientist Job Description – What Companies Look For in 2025

Pickl AI

Introduction In 2025, the role of a data scientist remains one of the most sought-after and lucrative career paths in India’s rapidly growing technology and business sectors. Cross-Functional Collaboration: Working closely with product managers, marketing teams, and domain experts to ensure data solutions address real business needs.

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Business Analytics vs Data Science: Which One Is Right for You?

Pickl AI

Summary: Business Analytics focuses on interpreting historical data for strategic decisions, while Data Science emphasizes predictive modeling and AI. Introduction In today’s data-driven world, businesses increasingly rely on analytics and insights to drive decisions and gain a competitive edge.

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Data Science Career FAQs Answered: Educational Background

Mlearning.ai

A good course to upskill in this area is — Machine Learning Specialization Data Visualization The ability to effectively communicate insights through data visualization is important. Check out this course to upskill on Apache Spark —  [link] Cloud Computing technologies such as AWS, GCP, Azure will also be a plus.

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8 Best Programming Language for Data Science

Pickl AI

It is popular for its powerful data visualization and analysis capabilities. Hence, Data Scientists rely on R to perform complex statistical operations. With a wide array of packages like ggplot2 and dplyr, R allows for sophisticated data visualization and efficient data manipulation. Wrapping it up !!!

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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

Proficient in programming languages like Python or R, data manipulation libraries like Pandas, and machine learning frameworks like TensorFlow and Scikit-learn, data scientists uncover patterns and trends through statistical analysis and data visualization. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

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Introduction to R Programming For Data Science

Pickl AI

Packages like stats, car, and survival are commonly used for statistical modeling and analysis. · Data Visualization : R offers several libraries, including ggplot2, plotly, and lattice, that allow for the creation of high-quality visualizations. that will help you enhance your efficacy and conduct data visualisations.