MACHINE LEARNING
Machine Learning course for Data Professionals using R, Python and Spark. This course covers topics such as fundamentals of Machine Learning, Research Analytics, along with implementation of Machine Learning principle using R, Python and Spark.
COURSE OBJECTIVE:
This Machine Learning course has been designed for Data Professionals to understand, represent and predict data more accurately. One will be able to use his/her existing talents with computing knowledge into Machine Learning Analysts having the capability of utilizing Machine Learning productively. Fundamentals of Machine Learning, Research Analytics, along with implementation of Machine Learning principle using R, Python and Spark, are covered in this course. |
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LESSON PLANS
COURSE A: FUNDAMENTALS OF MACHINE LEARNING SESSION 1: FUNDAMENTALS OF MACHINE LEARNING: Session Goal:
SESSION 2: MATH BEHIND MACHINE LEARNING: Session Goal:
SESSION 3: FUNDAMENTALS OF MATLABS/R PRACTICAL IMPLEMENTATION: Session Goal:
SESSION 4: MACHINE LEARNING ALGORITHMS: Session Goal:
SESSION 4: APPLYING MACHINE LEARNING: Session Goal:
COURSE B: RESEARCH ANALYTICS SESSION 1: RESEARCH ANALYSIS FUNDAMENTALS: Session Goal:
SESSION 2: RELIABILITY AND VALIDITY ANALYSIS: Session Goal:
SESSION 3: DATA CLEANING, IMPUTATION AND OUTLIER TESTING: Session Goal:
SESSION 4: HYPOTHESIS TESTING AND TEST OF DIFFERENCE: Session Goal:
SESSION 5: DESCRIPTIVE STATISTICS, CORRELATION AND REGRESSION ANALYSIS: Session Goal:
COURSE C: IMPLEMENTING MACHINE LEARNING PRINCIPLE USING R SESSION 1: INTRODUCING R: Session Goal:
SESSION 2: OPERATORS AND FUNCTIONS IN R: Session Goal:
SESSION 3: FUNDAMENTALS OF R GRAPHICS AND SUBSCRIPTING: Session Goal:
SESSION 4: WRITING FUNCTIONS IN R: Session Goal:
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SESSION 5: READING DATA FILES INTO R AND PRINTING USING FORMATTING: Session Goal:
SESSION 6: VECTORIZED PROGRAMMING AND MAPPING FUNCTIONS: Session Goal:
SESSION 7: STATISTICAL MODELING WITH R: Session Goal:
SESSION 8: BIG DATA ANALYTICS: Session Goal:
COURSE D: IMPLEMENTING MACHINE LEARNING PRINCIPLE USING PYTHON SESSION 1: FUNDAMENTALS OF PYTHON: Session Goal:
SESSION 2: WORKING WITH STATISTICS AND PROBABILITY USING PYTHON: Session Goal:
SESSION 3: MACHINE LEARNING WITH PYTHON: PART 1: Session Goal:
SESSION 4: MACHINE LEARNING WITH PYTHON: PART 2: Session Goal:
COURSE E: IMPLEMENTING MACHINE LEARNING PRINCIPLE USING SPARK SESSION 1: FUNDAMENTALS OF SPARK - 1: Session Goal:
SESSION 2: FUNDAMENTALS OF SPARK - 2: Session Goal:
SESSION 3: IMPLEMENTING MACHINE LEARNING ALGORITHMS IN SPARK -1: Session Goal:
SESSION 4: IMPLEMENTING MACHINE LEARNING ALGORITHMS IN SPARK -2: Session Goal:
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CASE STUDY AND PROJECTS:
Case studies are Integral part of Training. As part of this course we will ensure you implement Real-time case studies in various domains which includes:
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TRAINING FEATURES:
1) Extensive Real Time Live Examples, Projects & POCs for improved practical competency, ensure deployment readiness and implementation. 2) Custom Lab, Software and Environment provided with Real-time Project Simulation. 3) Recorded Videos complemented with corresponding lecture ppts, materials & lab guides. (Provided in the form of MP4 videos, pdf, ppt for offline access as well). 4) Certification and Job-Interview Counselling & Coaching after every training. |