• views: 278
• date: 17 July 2026
• posted by: voska89

Build and deploy Machine Learning models from scratch, covering Linear Regression, Decision Trees, Random Forests, and advanced Classification techniques.
Harness the power of Data Visualization with libraries like Matplotlib and Seaborn to communicate complex insights through professional, interactive charts.
Apply Big Data techniques and AI-driven automation to solve practical business problems, creating a high-impact portfolio to showcase to top employers.
core Data Science concepts including Exploratory Data Analysis (EDA), Statistical Inference, and Predictive Modeling using Python and real-world data.

Requirements

No prior Data Science or programming experience is required! We start from the absolute basics. A computer with an internet connection and a desire to learn are all you need to get started.

Description

This course contains the use of artificial intelligence
Become a Data Scientist from scratch and master the complete Data Science workflow with one comprehensive course. Whether you are a beginner, student, working professional, business analyst, software developer, or aspiring AI engineer, this course will help you build the skills required to succeed in the rapidly growing field of Data Science.
In this course, you will start with the fundamentals of Data Science, statistics, probability, and mathematics before diving into Python programming, NumPy, Pandas, data manipulation, and exploratory data analysis (EDA). You will learn how to collect, clean, transform, and analyze data to uncover meaningful insights.
As you progress, you will master SQL for data analysis, data visualization using Matplotlib, Seaborn, Plotly, and Power BI, and build machine learning models using Scikit-Learn. You will explore supervised and unsupervised learning techniques, including Linear Regression, Logistic Regression, Decision Trees, Random Forests, Support Vector Machines, Clustering, and more.
The course also covers advanced topics such as Deep Learning, Neural Networks, Computer Vision, Natural Language Processing (NLP), Large Language Models (LLMs), Generative AI, and MLOps. You will gain hands-on experience through practical exercises, case studies, and real-world projects that simulate industry scenarios.
By the end of this course, you will be able to confidently analyze data, build predictive models, deploy machine learning solutions, create professional dashboards, and apply Data Science techniques to solve business problems. You will also develop a portfolio of projects that can help you prepare for Data Scientist, Data Analyst, Machine Learning Engineer, and AI Engineer roles.
Join now and start your journey toward becoming a professional Data Scientist in 2026 and beyond.

What you'll learn

- Master Python programming for Data Science and Machine Learning.
- Perform data cleaning, preprocessing, analysis, and visualization.
- Build and evaluate machine learning and deep learning models.
- Work with SQL databases and real-world datasets.
- Create professional dashboards and data visualizations.
- Apply NLP, AI, and Generative AI techniques.
- Deploy and monitor machine learning models.
- Complete real-world Data Science projects from start to finish.

Who this course is for

This course is designed for aspiring Data Scientists, students looking to break into tech, or professionals in finance and marketing who want to use data-driven insights to make better business decisions.




   
   
   

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