Training Section - Data Science
Embark on a targeted exploration to acquire industry-specific expertise in our Data Science Course. Tailored for biotech and pharmaceuticals, you'll master data acquisition, exploratory analysis, model building, and practical application. Let's shape data excellence for your sector!
Objectives
The objectives of this course are to equip you with a strong foundation in data analysis techniques tailored to the biotech, pharmaceutical, and chemical industries.
By the end of this module, you will be able to:
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Understand the process of data acquisition and pre-processing.
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Master exploratory data analysis (EDA) through descriptive statistics.
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Build data-driven models and confidently interpret their results.
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Explore advanced data-driven models relevance to the biotech industry.
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Apply your newfound skills in an end-to-end data analysis scenario.
These objectives will guide your learning journey in Module 1, ensuring that you acquire essential data analysis skills specific to your industry.
Course
Overview
1
Data acquisition and pre-processing
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Sources of data in the biotech, pharmaceutics, and chemical industries.
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Cleaning and normalization techniques.
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Handling missing data.
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Data alignment.
2
Exploratory Data Analysis (EDA)
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Descriptive statistics and visualization techniques.
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Principle Component Analysis (PCA).
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Linear Discriminant Analysis (LDA).
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Interpretation of results.
3
Data-driven Models I
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Multiple Linear Regression (MLR).
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Partial Least Squares Regression (PLS-R).
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Support Vector Machines (SVM).
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Interpretation and application.
4
Data-driven Models I
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Introduction to neural networks.
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Architectures and applications.
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Deep learning techniques and its relevance to the biotech industry.
5
Step-by-step Example
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End-to-end data analysis using real or simulated data.
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Applying techniques learned from previous sessions.
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Interpretation and presentation of results.
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