Data Science & Machine Learning Techniques
This course has been designed to help students learn about complex theory, algorithms, and coding libraries for Machine Learning and their applications. This course provides a broad introduction to machine learning, data science techniques, and statistical pattern recognition. A certificate of completion is provided by Thinklogix at the end of the course.
This course has been designed to help students learn about complex theory, algorithms, and coding libraries for Machine Learning and their applications.
Machine learning is based upon the science of making computers act without being explicitly programmed. Some of the applications that use machine learning are virtual assistants like Siri, self-driving cars like Tesla, and email spam detection such as those employed by Gmail.
This course will teach machine learning models which are typically combined to solve complex problems. It will provide a broad introduction to machine learning, data science techniques, and statistical pattern recognition. Any machine learning application starts by analyzing the data and popular ETL techniques will be covered to transform data into a suitable form that may be used as an input for various machine learning algorithms. Topics include:
(i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks)
(ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning)
(iii) Hands-on experience building state-of-the-art image classifiers and other models using Python libraries like Keras in the real world.
By the end of this course, students will acquire the skills necessary to start creating their own AI applications. Upon course/certification completion, students will be mentored by ThinkLogix instructors and management in their future job search and career growth.
Price: CA$ 1,950
Course Stream: Data Science
Delivery method: Live instructors through online platforms
Prerequisites: Basic programming knowledge or STEM background
Flexi pay: Option to pay in installments
Paid internships available for students who successfully pass the course.
- Upcoming start date: October 15, 2022
- Course duration: 20 hours
- Lecture duration: 1 Month
- Students will receive ThinkLogix Certification upon course completion
- Students will receive Data Science Stream Certification upon completion of (i) Data Science and Machine Learning Techniques, and (ii) Python for Data Science
Ajitpal is a professional with over 10 years of experience working in data analysis and strategic management. Currently, he works as TimeLabs’s Data Analyst, and work towards building and improving products and services for our customers by using advanced analytics, ad-hoc analysis, consulting, creating data models and workflows, and onboarding compelling new data sets.
His previous experience includes a position as a Sr. Data Analyst at Tara Health Foods, where he worked with marketing, finance and logistics departments to analyze data for their logistics and retail network to look for the bottlenecks in the supply chain, production cycle planning, supplier network, discounting, marketing penetration analysis and financial analysis.