01
Industry-Focused Python Training
Learn Python programming with a strong focus on data science, analytics, automation, and real-world problem solving.
Data Science Training
Data Science with Python
Data Science with Python Professional Training.
Duration · 60 HoursLevel · Beginner
Course Overview
Data Science with Python Training is designed for students, graduates, working professionals, and technology enthusiasts who want to build a strong career in data science and analytics. Python has become one of the most widely used programming languages for data analysis, machine learning, automation, and artificial intelligence. This program provides learners with a structured pathway to understand Python programming, data analysis, visualization, statistics, and machine learning concepts.
The training focuses on practical learning through coding exercises, real-world datasets, data visualization, statistical analysis, and machine learning projects. Participants gain hands-on experience with popular Python libraries and learn how to transform raw data into meaningful insights. The program also helps learners develop the practical and analytical skills required for roles such as Data Analyst, Data Scientist, Python Developer, Machine Learning Engineer, and Business Intelligence Analyst.
Modules Covered
01Python Programming Fundamentals
02NumPy and Pandas
03Data Cleaning and Preprocessing
04Data Visualization
05Statistics for Data Science
06Exploratory Data Analysis
07Machine Learning Fundamentals
08Supervised Learning
09Unsupervised Learning
10Real-World Data Science Project
Course Details
Duration
60 Hours
Level
Beginner
Why Choose Our Data Science with Python Training?
02
Hands-On Data Analysis
Work with real datasets and learn how to clean, transform, analyze, visualize, and interpret data using Python.
03
Practical Machine Learning
Understand the fundamentals of machine learning and implement practical algorithms using Python.
04
Real-World Projects
Build practical projects that help you understand the complete data science workflow from raw data to actionable insights.
05
Career & Placement Guidance
Get support with interview preparation, resume development, portfolio building, and career preparation for data-driven technology roles.
What You Will Learn
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Build a strong foundation in Python programming for data science.
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Work with NumPy and Pandas for efficient data manipulation and analysis.
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Clean, transform, and preprocess real-world datasets.
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Create meaningful charts and visualizations from complex datasets.
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Understand statistical concepts used in data science.
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Perform exploratory data analysis to discover patterns and trends.
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Understand machine learning concepts and practical algorithms.
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Build and evaluate basic predictive models using Python.
Tools & Technologies
Python
NumPy
Pandas
Matplotlib
Seaborn
Scikit-learn
Practical Projects
Sales Data Analysis
Analyze business sales datasets to identify trends, patterns, performance indicators, and useful business insights.
Customer Analytics
Explore customer data to understand behavior, segmentation, and important patterns using Python.
Data Visualization Dashboard
Transform raw datasets into meaningful visualizations that make complex information easier to understand.
Machine Learning Prediction
Build a basic predictive model using Python and machine learning techniques to solve a real-world problem.
Career Opportunities
✓Data Scientist
✓Data Analyst
✓Python Developer
✓Machine Learning Engineer
✓Business Intelligence Analyst
✓Junior Data Engineer
Who Should Attend?
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Students who want to start a career in Data Science.
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Graduates looking to enter data-driven technology roles.
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Working professionals interested in transitioning into Data Science.
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Python developers who want to expand into Data Analytics and Machine Learning.
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Professionals interested in Artificial Intelligence and Machine Learning.
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Anyone interested in learning practical data analysis using Python.
Data Science with Python
Start Your Data Science Career
Learn Python, data analysis, visualization, statistics and machine learning through practical, project-based training.