Data Science For Everyone: From Zero To Pro
Published 7/2025
Created by Kusum Kumari
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 21 Lectures ( 8h 33m ) | Size: 3.88 GB
Understand the core concepts of data science and how it applies in real-world scenarios.
Gain a strong foundation in Python programming for data analysis and machine learning.
Clean, transform, and visualize data using Pandas, NumPy, Matplotlib, and Seaborn.
Query and manage data with SQL and connect to real-world databases.
Requirements
Basic understanding of mathematics, including: High school-level algebra Basic statistics (mean, median, standard deviation)
Some familiarity with programming concepts: Variables, loops, and functions Experience with any language (Python, Java, C++, etc.) is helpful - Python preferred but not required.
Description
This comprehensive Data Science course is your all-in-one guide to becoming a job-ready data professional - even if you're starting from scratch.You'll go from beginner to advanced, learning everything from Python programming and data visualization to building real-world machine learning models. Through interactive lessons and hands-on projects, you'll gain the practical skills and confidence to work with data, solve real business problems, and build a career in data science.Whether you're aiming to become a Data Scientist, Data Analyst, Machine Learning Engineer, or just want to use data more effectively in your current job - this course will give you the tools to succeed.Python programming for data analysisWorking with data using NumPy, Pandas, Matplotlib, and SeabornWriting SQL queries to extract insights from databasesStatistics & probability for data-driven decision-makingMachine learning with Scikit-learn: regression, classification, clusteringIntroduction to Deep Learning, NLP, and Time Series AnalysisBuilding and presenting real-world data science projectsPreparing for data science job interviews and building a professional portfolioPython, Jupyter Notebooks, Google ColabPandas, NumPy, Matplotlib, Seaborn, Scikit-learnSQL (PostgreSQL or MySQL)Real datasets from Kaggle, UCI, and open APIsBy the end of this course, you'll have built a strong portfolio, mastered the essential data science workflow, and be ready to land your first job or freelance opportunity in the data space.
Who this course is for
Anyone looking to start a career in data science, machine learning, or AI.
Students or graduates of any field (engineering, finance, biology, business, etc.) ready to transition into tech.
Data Science For Everyone: From Zero To Pro
