The course introduces participants to data pre-processing and data wrangling techniques & ML & AL algorithms. Participants are taught supervised and unsupervised techniques along with Decision Trees and Random Forest techniques. All the concepts taught will be followed by hands on exercises using codeless tools.
The pedagogy of the course has been designed to suit Graduates from any discipline. A unique feature of the course is the use of codeless methodology eliminating the need for learning programming languages like Python or R which by themselves take several months to learn and become hands on.
The codeless methodology will enable participants to quickly understand the concepts and get first hand on experience and acquire the necessary skills to pursue a career in Machine Learning and Artificial Intelligence.
✔ Understand and learn Data Pre-Processing & Data Wrangling techniques including feature engineering and feature extraction.
✔ Understand & learn Supervised and Unsupervised learning techniques.
✔ Understand & learn Decision Trees and Random Forest algorithms.
✔ Learn metrics for evaluation of the models.
✔ Develop the skills to analyse the data & build appropriate models.
✔ Get hands on experience in completing projects using the codeless methodology understand and learn how to classify data types such as structured, unstructured and semi-structured data
Unique Teaching-Learning Process-4C methodology
The course follows a unique 4-C methodology to provide sound conceptual knowledge delivered through online instructor-led sessions accompanied by home assignments which provide scope for analysing problems and solving them using the conceptual knowledge learnt during the course.
Joint Certification from GNDP and Sudaksha
Complete all the modules in the course successfully to receive the Certification
Top skills you will learn from the course
Statistics, Visualization, Predictive Analytics, Basic & Advanced Machine Learning and Deep Learning concepts. Using ML, AI and Deep Learning algorithms to solve problems and cases using the codeless methodology.
Frequently asked questions
Why Codeless Methodology?
Why is the Codeless Methodology Being Advocated?
The codeless methodology helps in solving ML/AI problems without going through the time consuming route of learning a programming language like Python / R.
What are the Trends in Codeless Methodology?
What are the Dfferent Codeless Tools Available?
There are several tools available and some of them are open source, that can be downloaded free of cost and practiced.
How can the Codeless Tools Help us Learn Data Science?
The participants will be taught the theoretical concepts in Statistics, Maths and Data Science / ML/ AI algorithms.The codeless tools will then be used to solve problems , use cases and projects.
Is it Difficult to Learn the Codeless Tools?
Does this Course Suit Participants from Non-technical Backgrounds?
View the general Frequently Asked Questions(FAQs) here
Srinivasa Rao is an Engineering Post Graduate from IIT Chennai and an MBA from IIM Kozhikode. He is a practicing Data Scientist with an overall experience of 25+ years in diverse domains such as the public sector, finance, retail, biometrics, health, manufacturing & energy sectors.
He currently works on building Machine Learning and AI solutions in sectors such as retail, manufacturing and energy sectors.