(DS04) All Data Science
The course is combination of both theory and practical component, and is up-to-date with the latest research and trends in Data Science. For example, it covers topics such as Representation Learning (new emerging field with-in Machine Learning), Deep Learning, Feature Engineering (secret sauce behind all practical and effective algorithms), Data Engineering and Machine Learning Engineering (marriage of Big Data world of databases and data with Machine Learning world of Analytics and models).
The course builds from the fundamentals and provides contents in sequential manner. It starts by introducing mathematical and programming fundamentals. It later covers traditional Machine Learning topics and then dive into Deep Learning. Finally, it introduces current trends in big data and big data analytics and concludes with Machine Learning Engineering topics.
- Complete/deep understanding of three facets of data science – Machine Learning, Deep Learning and Machine Learning Engineering.
- Knowledge of converting any problem at hand into data science constructs and identifying the right strategy to implement machine learning model.
- Understanding of what is under-the-hood of most data science models.
- Exposure to most problems that typical data scientists encounter.
- Informs attendees about the breadth and depth of topics in Data Science
- Providing expertise on the use of Scikit-learn, Tensorflow, Apache Spark, AWS, Microsoft Azure to solve challenging problems
- Informs attendees about upcoming and latest trends in Artificial Intelligence
- Day 1:Introduction, Programming Fundamentals, Mathematical Background and Supervised Machine Learning
- Day 2: Supervised Machine Learning (Contd), Time Series Analysis, Model Selection, Feature Engineering and Unsupervised Machine Learning
- Day 3: Deep machine Learning (ANN 2.0) and Representation Learning
- Day 4: Deep Learning – CNN and Deep Learning – RNN
- Day 5: Data Generation, Deep Reinforcement Learning and Big Data Engineering
- Day 6: Large Scale Machine Learning Platforms, Machine Learning Engineering I – Infrastructure and Machine Learning Engineering II – models
The price listed is the total price including GST where GST is applicable.
|(DS04) All Data Science (AESTime)||Saturday Sessons from 31 Oct to 5 Dec 2020||08:30 am - 04:30 pm||On Line||$5,500.00|
|(DS04) All Data Science||18 - 23 December 2020||08:30 am - 04:30 pm||Adelaide||$5,500.00|
NOTE: Courses are subject to cancellation if insufficient student numbers.
You will be notified a minimum of 4 weeks prior to the course commencement.
You will not be charged until the course is confirmed.