Use Python numerical, machine learning and NLP libraries such as scikit-learn, NumPy, SciPy, Gensim and NLTK to mine datasets and predict patterns.
Build statistical models — classification and clustering — that generate usable information from raw data.
Master the basics of data science and machine learning and harness the power of data to forecast what’s next.
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Bill has over 10 years of experience in the field of data science wih 5+ years as corporate trainer. He has previously worked across multiple verticals, including business, analytics boutiques, IT establishments and FMCG industries. He is an expert in machine learning and natural language processing with deep knowledge of computational complexity theory. He has a PhD in Cognitive Science and a MSc in Computational Linguistics, as well as many years of experience in statistical data analysis and software development in Python. He has extensive experience in developing software in pure Python as well as in C/C++, with a focus on the implementation of machine learning algorithms and statistical techniques.
Amril currently works as the Chief Architect at a leading telecom analytics solutions provider. He has 15 years of experience in managing Artificial Intelligence and Big Data related projects from both academic and industry. As the Chief Architect, he has led and managed USD$150M+ data science & big data technical project delivery and operational teams for the Company’s Telecommunication Traffic Monitoring and Tax Revenue Assurance system, which processes 20+ billion of CDR (Call Detail Records) transactions with an average of 4 Terabytes of binary and text data on a daily basis from telecommunication operators in India, Ghana, Guinea, and Sierra Leon. He has conducted extensive data science training classes to students for the last 5 years in the Middle East. He earned his PhD in Computer Science from the University College London (UCL), UK.
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Given the prevalence of technologies and the amount of data available in the online world about users, products, and the content that we generate, businesses can be making so much more well-informed decisions if this vast amount of data was more deeply analyzed through the use of data science. The data science course provides the tools, methods, and practical experience to enable you to make accurate predictions about data, which ultimately leads to better decision-making in business, and the use of smarter technology (think recommendation systems or targeted ads).
This course will provide you with technical skills in machine learning, algorithms, and data modeling which will allow you to make accurate predictions about your data. You will be creating your models using Python so you will gain a good grasp of this programming language. Furthermore, you will learn how to parse and clean your data which can take up to 70% of your time as a data scientist.
Individuals who have a strong interest in manipulating large data sets, finding patterns in data, and making predictions.
Basic knowledge in computing / statistics is recommended for this course. Knowledge in Python programming will be useful but not necessary.