Data Science For Biology/BioInformatics

The "Data Science for BioInformatics" course is for those who want their future at R&D departments of Pharmaceutical,Agricultural and Medical Industries.

For secure job and successful career it is essential to learn Data Science for Bio perspective because in bio their is curse of Big Data that can be handled and analysed easily through Data Science. From Machine learning tool a machine can learn from the data, identify patterns, and make predictions or generate hypotheses.It has become possible to accurately predict number of diseases through ML. Explore more about the course from below link.

Key Highlights

   Course is only specific to Bio Students.

   Statistics and Quantitative Methods are practically employed through this course to analyse multiple datasets.

   Know how to handle bio research project with large dataset of genes,cells,X-rays etc.

   Placement assistance in medium to big level firms.

   Our Learning Management System offers AI-assisted problem-solving and simulates technical interviews.

   We offers a flexible schedule, enabling students to adapt their study hours.

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Why To Choose Theta Academy?

Who Is This Program For?

This Program is for those guys who are currently pursuing degree/diploma in Biotechnology/Bioinformatics/pharma/agriculture/food technology etc. Or those who are currently working professionals in this Industry.

Job Opportunities post AI & Machine Learning Course

A Student of bio after doing our data science course can pursue careers as Biostatistician,Pharmaceautcal Data Analyst,Epidemiologist,Regulatory Affairs Analyst , Genetic Counselor or Researcher at Top Biotech companies.

Top Subjects You will learn

Bio-Python,Singe Cell Analysis Framework, R Programming,Bio-Medical Imaging,Machine Learning,BioSQL

What are the minimum requirements for course?

This course is only for those who are currently pursuing or completed the BSC/BTECH/DIPLOMA/Master's in any subfield of bio.Working Professionals or PHD students are also eligible and have special support for them.

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Our Industrial Projects

Deep Learning based prediction,identification,assessment of the quality of three grain crops

Using approx. 23,000 photos, students created labeled imaging data on the germination of more than 2400 seeds for three different crops: Zea mays (maize), Secale cereale (rye), and Pennisetum glaucum (pearl millet). Transfer learning has been used with area proposals to predict whether or not the seeds will sprout.

Autism Mutation Detection using Deep Learning

To address the difficulty of determining the influence of noncoding mutations on disease, this project predicts the precise regulatory effects and the detrimental repercussions of genetic variants. Predictive genomics emphasizes noncoding mutations in ASD and investigates variants with stronger effects for further investigation in the future.

DNA Sequence Classifier

Buy And Sell Popular Digital Currencies, Keep Track Of Them In The In this project, you will employ a classification model that can infer a gene's function just from the DNA sequence of the coding sequence. You will write a function that, using scikit-learn NLP tools, will extract from any sequence string all overlapping k-mers of a specified length, count the k-mers, and transform the list of k-mers for each gene into string sequences.

Curriculum Designed by Experts

  • Python Programming

    13 Topics
    Topics
    • Data types
    • Conditions and loops
    • File and Exception Handling
    • Object Oriented Programming
    • Chat GPT with Python
    • Advanced Python
    • Database Management System
    • CRUD Operations
    • Joins
    • Advance SQL
  • Topics
    • Handling Sequences and Alignment with BioPython
    • Working with FASTA,GENBANKS
    • 3D Structures
    • Basic Local Alignment Search Tool
  • Topics
    • Biological Databases and Analytics
    • Feature Engineering
    • Machine Learning
    • Deep Learning
    • Structural/Functional Genomics
  • Topics
    • Basics of Computer Vision
    • CNN
    • Cancer detection system using Segmentation and CNN models
    • Advance Image Processing

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FAQ'S

  • Why should I learn Data science in Biology/Bio-Informatics ?

    • With advancements in technology, biology has become increasingly data-intensive. From DNA sequencing to gene expression analysis, researchers generate massive datasets. Data science provides the tools and techniques to handle, analyze, and extract valuable insights from these large datasets efficiently.
    • Data science plays a crucial role in the field of precision medicine, which tailors medical treatments to individual patients based on their genetic makeup and other relevant factors.
    • Biology generates data from various "omics" technologies like genomics, transcriptomics, proteomics, and metabolomics.Data science provides the necessary tools to process, integrate, and analyze multi-omics data.
    In conclusion, data science is essential for biology and bioinformatics students as it empowers them to tackle complex biological problems, extract meaningful information from data, and contribute to various fields of biology and medicine, ultimately advancing scientific knowledge and improving human health.

  • Yes, you can learn programming easily. Start with a beginner-friendly language like Python, use online class, and practice regularly to build your skills. Stay persistent and patient with yourself as you progress.
    At THETA ACADEMY all courses are designed for those who just step into technology(Begineer level)

  • Yes,THETA ACADEMY can provide Internship certificate.In our courses we provide industrial level training and capstone projects are done.A Student who enroll in the course can recieve internship certificate at the end of course. The only rule is he/she have to submit his/her proof of College.

  • In this course, while some basic mathematical concepts are essential, you don't need to be a math expert to get started. Data science and Bio-Informatics course involves using statistical methods, algebra, and calculus for analysis and modeling. Don't worry if you find math challenging; the focus will be on practical applications and understanding how to work with data effectively. We will cover mathematical topics in such a way that a non mathematic lover can also join it.As you progress, you'll gain a deeper understanding of the necessary mathematical principles and their role in data analysis

  • Course content is designed to align with international standards and practices, ensuring that the knowledge and skills gained will be applicable and valued in foreign universities. If you are going to pursue Bio-Informatics at Foreign, It is mandatory in their syllabus to learn Python or R.So Learning this before going will assist you.

Our Student Reviews

Data Science in Biology and Bio Informatics

The amount of data in the modern world is expanding quickly, and biology is one of the major drivers of this growth. Millions of data points on proteins, genes, tissues, etc. are frequently stored and integrated for systemic investigations in biological data science. However, established methods like computational biology find it difficult to identify useful patterns from this data due to its volume and complexity. Therefore, it is vital to employ cutting-edge methods in order to address such pressing issues on a worldwide basis.