CCMAS Course Search

Basic concept and types of traverses. Temporary and permanent adjustment of traverse instruments (Theodolite, EDM, Total Station and GPS). Field observations, Forward, Backward and area computations in traversing. Elementary adjustment of traverse network. Production of traverse plan at a suitable scale. Sources of errors and accuracy attainable in traversing. Basic concept, method and uses of leveling. Leveling with inverted staff, double and reciprocal leveling. leveling data collection, computation and elementary adjustment of level network. Sources of errors, corrections and accuracy attainable in leveling. Principles, special features and uses of tachometry. Field observations, computations and production of plans at suitable scales from tachometry. Substance bar and its uses.

General introduction to the various facts of land surveying, determination of vertical distance errors, and corrections in levelling cross-sections and profiles: contouring, enlargement and reduction of maps, years. Introduction to Geographic land information systems, use of basic GPS devices.

Batch calculation methods; arithmetical approximation, method of simultaneous equation, computerized batch calculation, supplementary information relating to glass composition and batch calculations. Provision of basis for evaluation of raw material; introducing raw or modified batches into the operation; taking samples for control analysis. Batch handling and preparation method.

Sampling theory and its critique; subjective probability; likelihood principles; Bayes theorem; Bayesian analysis of Normal theory inference problems; the Behrens-Fisher problem; assessment of model assumptions; robustness of inference; analysis of variance; estimation of variance components; empirical Bayes; some aspects of multivariate problems; sequential nature of Bayesian inference; prior and posterior distributions of parameters in binomial; poisson; exponential and normal populations; comparison of two normal distributions; predictive distributions; decision theory; utility; risk aversion; extensive form of analysis; two-action problems; point estimation; best population problems; economics of sampling

Beer stabilization methods. Clarification and filtration techniques. Exclusion of air. Chilling and carbonating. Container filling and sealing equipment and their operating principles Pasteurization and other methods of beer stabilization. Physical and chemical properties of beer. Beer sensory evaluation. Maintenance of equipment and corrective measures for variance in packaged product quality.

Beer stabilization methods; Clarification and filtration techniques; Exclusion of air; Chilling and carbonating; Container filling and sealing equipment and their operating principles; Pasteurization and other methods of beer stabilization; Physical and chemical properties of beer; Beer sensory evaluation; Maintenance of equipment and corrective measures for variance in packaged product quality

Advanced studies of the adaptive value of social organization; territory; reproductive ecology; feeding ecology; predator/prey interactions and competition; Case studies

Installation: Cloudera VM, Jupyter server. Big data retrieval and relational querying: Postgres databases, NoSQL data, MongoDB, Aerospike, and Pandas for data aggregation and working with data frames. Big Data Integration: Splunk and Datameer. Big Data Processing: Apache Spark, Hadoop, Spark Core (Spark MLlib and GraphX). Big Data Applications (Graph Processing). Big Data Streaming Platforms for Fast Data. Lab Work: Analysing Twitter Data using Spark and MongoDB. Learn Big Data analytics skills. Practical procedure for the crafting of an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from data. Use the practical exercises to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. Hands-on exposure to Hadoop and Spark (or any of the BD tools), build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases. Practical assignment of BD security.

Introduction to microbiology and biochemistry. Classification and growth characteristics of micro-organisms. Enzymes Engineering: including enzyme kinetics, aerobic and anaerobic respirations, metabolic pathways, cell growth kinetics and models

Gene cloning and the application of recombinant DNA technology in medicine. Application of immunotherapy. Molecular and cell biology. DNA, replication and transcription. RNA and relationship to DNA. Genetic code. Biosynthesis of protein and regulation of gene expression. Tools of genetic engineering (molecular biology). Hybridisation, molecular cloning, southern blotting and related techniques, polymerase chain reaction (PCR) and its application to medicine. Molecular and biochemical basis of inheritance of common diseases, 205 haemoglobinopathies. Gene therapy. Biochemical aspects of cancer and cancer therapy. Personalized medicine.