Course Date
20th August 2023
Duration
40 hrs.
Delivery Format
Online Live
Why to Join This Course
Join Our Data Scientist Today!
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Course Price
₹8,999.00
Key Features
Curriculum for Data Scientist
Module 1: Advanced Statistical Analysis (10 hours)
- Hypothesis testing and confidence intervals
- Analysis of Variance (ANOVA)
- Non-parametric statistics
- Time series Analysis
- Multivariate Analysis techniques
- Hands-on project: Analyzing real-world datasets using advanced statistical techniques.
Module 2: Machine Learning Techniques and Model Interpretation (10 hours)
- Regression models (linear regression, logistic regression)
- Decision trees and random forests
- Support Vector Machines (SVM)
- Ensemble methods (bagging, boosting)
- Model interpretation and Feature importance
- Hands-on project: Implementing and evaluating machine learning models for classification and regression tasks.
Module 3: Data Visualization and Storytelling (10 hours)
- Principles of data visualization
- Exploratory data Analysis and visualization techniques
- Designing effective visualizations for different types of data
- Storytelling with data and creating compelling narratives
- Dashboard design and interactive visualizations
- Hands-on project: Creating impactful data visualizations and presenting insights through storytelling.
Module 4: Experimentation and A/B Testing (10 hours)
- Designing experiments and Hypothesis formulation
- Conducting A/B tests and analyzing results
- Statistical significance and power Analysis
- Experimental design for online platforms
- Interpreting experiment results and making data-driven decisions
- Hands-on project: Designing and conducting A/B tests on real-world scenarios.
Module 5: Real-World Case Studies (5 hours)
- Analyzing and addressing real-world data science challenges
- Applying learned concepts to solve practical problems
- Demonstrating proficiency in data-driven decision-making through case studies.
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Eligibility Criteria
For admission to this Professional Certificate course in Data Scientist Course, candidates should have:
- Basic Programming Knowledge
- Database Fundamentals
- Data Analytics Basics
- Mathematics and Statistics (recommended but not mandatory)
- Data Analysis Tools (e.g., Pandas, NumPy, SQL) (recommended but not mandatory)
Course Outcomes
Upon completion of this course, students will be able to:
- Gain expertise in advanced statistical analysis, including hypothesis testing, ANOVA, and time series analysis, enabling meaningful insights from complex datasets.
- Acquire practical knowledge in machine learning techniques like regression, decision trees, and support vector machines, along with understanding ensemble methods for classification and regression tasks.
- Interpret machine learning models and determine feature importance to make data-driven decisions and improve model performance.
- Master data visualization principles, design impactful visualizations, and create compelling narratives for effective data communication.
- Develop proficiency in experimentation and A/B testing, applying statistical significance and power analysis to make informed decisions and solve real-world data science challenges through case studies.

FAQ for Data Scientist Course
Admission Process
Submit Application
Tell us a bit about yourself and why you want to do this program
Application Review
An admission panel will shortlist candidates based on their application
Enrolment
Selected candidates can join the program by paying the admission fee