COURSE DESCRIPTION

Beginner Batch

Module 1 - Fundamentals of Analysis of Data

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Duration: 8 Weeks

The first step towards becoming a Data Analyst, Data Scientist, or ML Engineer is to have strong command over the fundamentals of visualization, dashboarding & reporting of data.

Within this module, our goal is to become confident in data fundamentals.

Topics that will be covered:

Excel

Introduction to Excel and Formulas
Pivot Tables, Charts and Statistical functions
Google spreadsheets
Beginner Python

Flowcharts, Data Types, Operations
Conditional Statements & Loops
Functions
Strings
In-build Data Structures - List, Tuples, Dictionary, Set, Matrix Algebra, Number Systems
Tableau / PowerBI

Visual Analytics
Charts, Graphs, Operations on Data & Calculations in Tableau/ PowerBI
Advanced Visual Analytics & Level of Detail (LOD) Expressions
Geographic Visualizations, Advanced Charts, and Worksheet & Workbook Formatting
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USPs of our Delivery

All topics taught in live classes with limited batch size helping in instant doubt support to accelerate learning.
Assignment (post-lecture) & their evaluation.
Hyper-Personalised: Special focus on the individual with a constant touch from student success manager & mentor.
Start your Data Science journey .

Advance Batch

Module 1 - Foundations of Machine Learning & Deep Learning

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Duration: 10 Weeks

Mathematics is the foundation upon which Machine Learning & Deep Learning algorithms are built.

That is why, in this module, you will fall in love with mathematics as you solve engaging problems & build your solid foundations of Machine Learning & Deep Learning.

Topics that will be covered:

Advanced Python & Python Libraries:

Python Libraries

Python Refresher
Numpy, Pandas
Matplotlib
Seaborn
Data Acquisition
Web API & Web Scrapping
Beautifulsoup & Tweepy
Advanced Python

Basics of Time & Space Complexity
OOPS
Functional Programming
Exception Handling & Modules
Maths for Machine Learning:

Probability & Applied Statistics

Probability
Bayes Theorem
Distributions
Descriptive Statistics, outlier treatment
Confidence Interval
Central Limit Theorem
Hypothesis Test, AB Testing
ANOVA
Correlation
EDA, Feature Engineering, Missing value treatment
Experiment Design
Regex, NLTK, OpenCV
Calculus, Optimization & Linear Algebra

Classification
Hyperplane
Halfspace
Calculus
Optimization
Gradient Descent
Principal Component