Preamble: I've no substantial experience or knowledge where mathematics, biochemistry, biostatistics or computer science are concerned. I am a student of the HND IT and Computing diploma as governed by Edexcel, and I trust that core curriculum to provide the basics of Computer Science, networks and systems. I will go on to do my Bachelor's in the same program.
My motivation to self-study Bioinformatics is guided by knowing that my chances of getting into a BI master's programme when I finish my Bachelor's are slim to none. Before taking up IT and Computing, I was a biology major with no interest whatsoever in drawing plant morphology. Due to personal reasons I had to end my biology course with nothing to show for it but the finished courses in Chemistry 101, the basics of cell biology and tissue biology, some introductory physics, organic chem, some forgettable biostatistics and the systematics of invertebrates. Not an impressive array of biological knowledge.
As I am studying software development, data manipulation and slightly more involved mathematics, I turn naturally to the crux of information technology and biology: bioinformatics. Via courses offered at MIT Open Courseware, Coursera, Udacity and other individual institutions, using (partly) the 'Bioinformatics SelfStudy Curriculum' from PLOS, I will attempt to fill out the 'systematic gaps in knowledge' and work at getting an education approaching a proper undergraduate degree in Bioinformatics. My goal is to learn; I do not know whether any educational establishment would consider the self-study credentials. I do think they are the best way to learn about the field and not confine myself to the career paths prophecised by the Edexcel diploma records.
My (relevant) courses currently include:
- MIT: Multivariable Calculus
- MIT: Linear Algebra
- My college: HND Mathematics for software development
- Stanford: Machine Learning (Coursera)
- My college: HND Object-Oriented Programming
- John Hopkins Uni: Mathematical Biostatistics Bootcamp (Coursera)
- Biochemistry (NPTEL)
I start the following courses in January:
- University of Washington: Computational Neuroscience (Coursera)
- Paris School of Engineering: Discrete inference and learning in artificial vision (Coursera)
In February:
- Java programming
- Information systems
My motivation to self-study Bioinformatics is guided by knowing that my chances of getting into a BI master's programme when I finish my Bachelor's are slim to none. Before taking up IT and Computing, I was a biology major with no interest whatsoever in drawing plant morphology. Due to personal reasons I had to end my biology course with nothing to show for it but the finished courses in Chemistry 101, the basics of cell biology and tissue biology, some introductory physics, organic chem, some forgettable biostatistics and the systematics of invertebrates. Not an impressive array of biological knowledge.
As I am studying software development, data manipulation and slightly more involved mathematics, I turn naturally to the crux of information technology and biology: bioinformatics. Via courses offered at MIT Open Courseware, Coursera, Udacity and other individual institutions, using (partly) the 'Bioinformatics SelfStudy Curriculum' from PLOS, I will attempt to fill out the 'systematic gaps in knowledge' and work at getting an education approaching a proper undergraduate degree in Bioinformatics. My goal is to learn; I do not know whether any educational establishment would consider the self-study credentials. I do think they are the best way to learn about the field and not confine myself to the career paths prophecised by the Edexcel diploma records.
My (relevant) courses currently include:
- MIT: Multivariable Calculus
- MIT: Linear Algebra
- My college: HND Mathematics for software development
- Stanford: Machine Learning (Coursera)
- My college: HND Object-Oriented Programming
- John Hopkins Uni: Mathematical Biostatistics Bootcamp (Coursera)
- Biochemistry (NPTEL)
I start the following courses in January:
- University of Washington: Computational Neuroscience (Coursera)
- Paris School of Engineering: Discrete inference and learning in artificial vision (Coursera)
In February:
- Java programming
- Information systems
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