Data Analytics/Business Analytics
With the aim to provide the best in Data Science, we have designed a course that can be said to be one of the most comprehensive Data Science courses in Kolkata. Your search for the best Data Science course should end here as what we offer covers the complete Data Science life cycle concepts. We will teach you how to obtain data from all available sources, clean it to suit your purpose and explore it by extracting features in your data sets.We will also teach you how to use data visualization techniques. Then we teach you data modelling and also interpreting those models and data interpretation in layman’s terms so that your customer understands your solutions when you present it to them.
We cover the full range of skills and tools needed by data professionals to work in today’s industry. Check the course details given below to get an idea of the things you will learn. The course will be taught by well-known data scientists (all IIT,
ISB alumni) from the industry with years of experience providing data science solutions as well as training.
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We also provide placement assistance as part of the Data Science training program. Our students have been placed successfully in various national and multinational companies.
You too can be an accomplished data professional. Join us now!
Things You Will Learn
• Module 1 – SQL And RDBMS
• Module 2 – R & R Studio
• Module 3 – Introduction To Python
• Module 4 – Basic Python
• Module 5- Working With Libraries Like NumPy, Pandas, Matplotlib, Seaborn, SciPy, Sklearn In
Python
• Module 6 – Working Experience With Pandas In Python
• Module 7 – Working Experience With Matplotlib Library In Python
• Module 8 – To Work With Seaborn Library (High-Level Interface For Drawing Attractive And
Informative Statistical Graphics) In Python
• Module 9 – Introduction To SciPy And Sklearn Libraries In Python
• Module 10 – Statistical Analysis
• Module 11 – Hypothesis Testing
• Module 12 – Linear Regression
• Module 13 – Logistic Regression
• Module 14 – Discrete Probability Distribution
• Module 15 – Advanced Regression
• Module 16 – Multinomial Regression
• Module 17 – Data Mining Unsupervised – Clustering
• Module 18 – Dimension Reduction
• Module 19 – Data Mining Unsupervised – Network Analytics
• Module 20 – Data Mining Unsupervised – Association Rules
• Module 21 – Data Mining Unsupervised – Recommender System
• Module 22 – Machine Learning Classifiers – KNN
• Module 23 – An Introduction To Data Visualization
• Module 24 – Tableau Products And Usage
• Module 25 – Basic Charts On Tableau
• Module 26 – Connecting Tableau With Multiple Sheets And Data Sources
• Module 27 – Tableau Filters And Visualization Interactivity
• Module 28 – Interaction And Grouping The Data
• Module 29 – Time Series Chart
• Module 30 – Maps And Images In Tableau
• Module 31 – Advanced Charts In Tableau And Analytical Techniques
• Module 32 – Calculations On Tableau
• Module 33 – Tableau Integration With Other Tools
• Module 34 – Understand The Business Problem
• Module 35 – Data Collection
• Module 36 – Data Cleansing / Exploratory Data Analysis / Feature Engineering
• Module 37 – Data Mining
• Module 38 – Model Deployment
• Module 39 – Introduction To Big Data
• Module 40 – Hadoop And Its Components
• Module 41 – Linux OS And Virtualization Software
• Module 42 – Apache Hive
• Module 43 – Apache SQOOP
• Module 44 – Apache Spark
• Module 45 – Azure
• Module 46 – Classifier – Naive Bayes
• Module 47 – Bagging And Boosting
• Module 48 – Decision Tree And Random Forest
• Module 49 – Black Box Methods
• Module 50 – Text Mining
• Module 51 – Natural Language Processing
• Module 52 – Forecasting
• Module 53 – Assignments
• Module 54 – Projects