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Data Analytics Course

Course Detail

Data Analytics

Data Analytics

This Data Analytics Master’s Course will help you become an expert in the domain of Data Analytics. In this course, you will learn about data analytics, data transformation, Storytelling, optimization techniques, project execution strategies, data science, and data Visualization. This course is designed by industry experts with the Aim to make you job-ready.

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Syllabus

Module 1
  • Preparatory Sessions – Data Transformation using Ms. Excel & Python
  • Learn how to do data analysis, data transformation and other important data analysis functions.
  • Basic fundamental of Python and learn how to do data analytics using the same.
Module 2
  • Data wrangling with SQL
  • Introduction to SQL
  • Database normalization
  • Entity-relationship model
  • SQL operators
  • Join, tables, and variables
  • SQL functions
  • Subqueries
  • SQL functions, views, and stored procedures
  • User-defined functions
  • SQL performance and optimization
  • Advanced concepts
Module 3
  • Presto
  • Introduction to Presto
  • Writing Queries in Presto on large data sets.
  • Data Transformation using PrestoKey Takeaways
Module 4
  • Introduction to Data Science & Statistics
  • Descriptive Statistics
  • Introduction to Probability
  • Probability Distributions
  • Hypothesis Testing and Estimation
  • Goodness of Fit
Module 5
  • Business Problem Solving, Insights and Storytelling
  • Business domains
  • Understanding the business problem and formulating
  • hypotheses
  • Exploratory data analysis
  • Data storytelling: Narrate stories in a memorable way
  • Project on deriving business insights and storytelling
Module 6
  • Optimization Techniques
  • Linear programming
  • Goal programming
  • Integer programming
  • Mixed integer programming
  • Distribution and network models
Module 7
  • Introduction to KNIME
  • Working with data in KNIME
  • Loops in KNiME
  • Web scraping in KNIME
  • Hyperparameter optimization in KNIME
  • Hyperparameter optimization for Machine Learning
  • Models using loops in KNIME
  • Feature Selection in KNIME
Module 8
  • Statistics & Machine Learning using R
  • Programming
  • Programming with R
  • Advance Statistics
  • Data Mining
Module 9
  • Predictive Modeling
  • Multiple linear regression
  • Logistic regression
  • Linear discriminant analysis
Module 10
  • Time Series Forecasting
  • Introduction to time-series
  • Correlation
  • Forecasting
  • Autoregressive models
Module 11
  • Feature Engineering
  • Handling unstructured data
  • Machine learning algorithms
  • Bias variance trade-off
  • Handling unbalanced data
  • Boosting
  • Model validation
Module 12
  • Advance Machine Learning Techniques
  • Hyper parameter optimization
  • Advance Machine Learning Libraries – XGBoost
  • Solving Problems on Kaggle
Module 13
  • Data Science Execution Strategy
  • Framework to Data Science strategy
  • Mapping Data Science with data architecture strategy
  • Executing Data Science strategy
Module 14
  • Business Case Studies
  • Marketing & retail analytics
  • Social analytics
  • Logistics & supply chain
  • Financial analytics
Module 15
  • Visualization using Power BI
  • Introduction to Power BI
  • Data Extraction
  • Data Transformation – Shaping & Combining Data
  • Data Modelling & DAX
  • Data Visualizations with analytics
  • Power BI Service (Cloud), Q&A, and Data Insights
  • Power BI Settings, Administration & Direct Connectivity
  • Embedded Power BI with API & Power BI
  • Power BI Advance & Power BI Premium
Module 16
  • Data Science Capstone Project
  • In the Data Science & Business Analytics Capstone
  • Project, you will use all the knowledge and skills you have
  • Acquired throughout this advanced certification program
  • And get real world Industry project exposure

Career Opportunities

  • Big Data Developer
  • Data Scientist
  • Data Analyst
  • Data Engineer
  • Data Architect
  • Business Intelligence Analyst



Entry Qualification

  • Candidates will be admitted on the basis of interviews and / or group discussions.
  • 20% of the total seats will be reserved for SC, ST and OBC candidates.If the reserved seats are not filled within the specified period, the vacant seats will be offered to the general candidates.

Course Features

Instructor
Industry Experienced Trainer
Rating
4.9 (Google Review)
Study Mode
Offline & Online
Duration
4 month
Language
English, Bengali, Hindi
100% Job Assistance
Yes
Internship
Free & Paid
Course Price
Click to Know

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MD Kashid Hossain

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