Data Science Vs Data Analyst In 2024 | Skills, Career, Salary Comparision | Simplilearn [Video]

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Are you curious about the differences between Data Science and Data Analytics? In this video, we delve deep into the distinct roles, skills, and applications of these two exciting fields. Whether you’re a tech enthusiast, a student, or someone considering a career in data, this video will provide you with a clear understanding of Data Science and Data Analytics.

We start by defining what Data Science and Data Analytics are, and then move on to compare their key aspects. You’ll learn about the tools and techniques used in each field, the types of problems they solve, and the typical career paths for professionals in each domain.
Throughout the video, we provide real-world examples to illustrate how Data Scientists and Data Analysts contribute to their organizations. From predictive modeling and machine learning in Data Science to statistical analysis and data visualization in Data Analytics, we cover it all.

00:00 – Introduction to Data Analytics V/s Data Science
03:08 – Data Analytics V/s Data Science
04:53 – Comparing Data Science V/s Data Analytics
06:08 – Skill Set Comparison
06:48 – Workflow Comparison
08:42 – Tools and Techniques
10:13 – Application Comparison
11:32 – Carrer Path Comparison

✅What is the main difference between Data Science and Data Analytics?
Data Science focuses on creating new models and algorithms to predict future trends and drive innovation, while Data Analytics focuses on interpreting existing data to solve current problems and provide actionable insights.

✅What tools are commonly used in Data Science?
Common tools in Data Science include Python, R, Hadoop, Apache Spark, and TensorFlow for tasks such as data manipulation, machine learning, and AI.

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➡️ About Post Graduate Program In Data Analytics
This Data Analytics Program is ideal for all working professionals and prior programming knowledge is not required. It covers topics like data analysis, data visualization, regression techniques, and supervised learning in-depth via our applied learning model with live sessions by leading practitioners and industry projects.

✅ Key Features
– Post Graduate Program certificate and Alumni Association membership
– Exclusive hackathons and Ask me Anything sessions by IBM
– 8X higher live interaction in live online classes by industry experts
– Capstone from 3 domains and 14+ Data Analytics Projects with Industry datasets from Google PlayStore, Lyft, World Bank etc.
– Master Classes delivered by Purdue faculty and IBM experts
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– Resume preparation and LinkedIn profile building
– 1:1 mock interview
– Career accelerator webinars

✅ Skills Covered
– Data Analytics
– Statistical Analysis using Excel
– Data Analysis Python and R
– Data Visualization Tableau and Power BI
– Linear and logistic regression modules
– Clustering using kmeans
– Supervised Learning

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