Professional Diploma in Data Science
Curriculum
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Module 1: Introduction to Data Science and Machine Learning (Duration:10 hr)
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Module 2 – Python Programming and Data Manipulation (Duration:50 hr)
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Orientation
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Environment setup | Python Basics
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Data types and Variable assignments
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Conditional Statements and Loops
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Functions, Modules and Packages
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Mini Project Building (Practical)
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File Handling | Regular Expression
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Data manipulation with NumPy and pandas
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Object Oriented Programming
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Major Project Building (Practical)
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Module 3 – Introduction to SQL (Duration:30 hr)
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Module 4 - Data Visualization and Exploratory Data Analysis (Duration:30 hr)
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Module 5: Machine Learning Basics (Duration:20 hr)
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Module 6: Advanced Machine Learning Techniques (Duration:30 hr)
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Module 7: Introduction to Neural Networks and Deep Learning (Duration:30 hr)
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Module 8: Natural Language Processing (NLP) (Duration:20 hr)
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Module 9: Time Series Analysis and Forecasting (Duration:20 hr)
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Module 10: Capstone Project (Duration:30 hr)
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Module 11: Data Ethics and Privacy (Duration:20 hr)
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Module 12: Tools and Deployment (Duration:30 hr)
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Module 1: Introduction to Data Science and Machine Learning (Duration:10 hr)
-
Module 2 – Python Programming and Data Manipulation (Duration:50 hr)
- Orientation
- Environment setup | Python Basics
- Data types and Variable assignments
- Conditional Statements and Loops
- Functions, Modules and Packages
- Mini Project Building (Practical)
- File Handling | Regular Expression
- Data manipulation with NumPy and pandas
- Object Oriented Programming
- Major Project Building (Practical)
-
Module 3 – Introduction to SQL (Duration:30 hr)
-
Module 4 - Data Visualization and Exploratory Data Analysis (Duration:30 hr)
-
Module 5: Machine Learning Basics (Duration:20 hr)
-
Module 6: Advanced Machine Learning Techniques (Duration:30 hr)
-
Module 7: Introduction to Neural Networks and Deep Learning (Duration:30 hr)
-
Module 8: Natural Language Processing (NLP) (Duration:20 hr)
-
Module 9: Time Series Analysis and Forecasting (Duration:20 hr)
-
Module 10: Capstone Project (Duration:30 hr)
-
Module 11: Data Ethics and Privacy (Duration:20 hr)
-
Module 12: Tools and Deployment (Duration:30 hr)
Overview
Tools Covered
The Data Science Course at Asquare Technologies is an excellent starting point for technology enthusiasts aiming to build a career in data science. The course curriculum includes:
⦁ Introduction to Data Science: Overview of data science concepts and applications.
⦁ Python Basics and Libraries for Data Analysis: Fundamental Python programming skills and key libraries such as Pandas and NumPy.
⦁ Machine Learning: Training in algorithms and techniques for predictive modeling and data-driven decision-making.
⦁ Natural Language Processing (NLP): Techniques for processing and analyzing textual data.
⦁ Deep Learning: Advanced neural networks for complex data tasks.
⦁ Computer Vision and OCR: Image processing and Optical Character Recognition techniques.
⦁ Excel Basics: Foundational skills in data handling and analysis using Excel.
⦁ SQL: Essentials of querying and managing data in databases.
⦁ Power BI Fundamentals: Introduction to creating visualizations and dashboards with Power BI.
This course offers a comprehensive pathway for anyone eager to dive into the rapidly growing field of data science.
Certification
LET'S TALKFeel Free to Speak With Our Executive
Tools Covered
The Data Science Course at Asquare Technologies is an excellent starting point for technology enthusiasts aiming to build a career in data science. The course curriculum includes:
⦁ Introduction to Data Science: Overview of data science concepts and applications.
⦁ Python Basics and Libraries for Data Analysis: Fundamental Python programming skills and key libraries such as Pandas and NumPy.
⦁ Machine Learning: Training in algorithms and techniques for predictive modeling and data-driven decision-making.
⦁ Natural Language Processing (NLP): Techniques for processing and analyzing textual data.
⦁ Deep Learning: Advanced neural networks for complex data tasks.
⦁ Computer Vision and OCR: Image processing and Optical Character Recognition techniques.
⦁ Excel Basics: Foundational skills in data handling and analysis using Excel.
⦁ SQL: Essentials of querying and managing data in databases.
⦁ Power BI Fundamentals: Introduction to creating visualizations and dashboards with Power BI.
This course offers a comprehensive pathway for anyone eager to dive into the rapidly growing field of data science.
Certification
Feel Free to Speak With Our Executive
Instructor
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