Data Science
This program ensures a smooth transition into Jr. Data Scientist, Business Analyst, Data Analyst, Database Manager, and other relevant positions.
Python
1
Orientation
2
Basics of Computing
3
Computational Thinking
4
Environment Setup | Python Basics
5
Jupyter Notebook and Data Types
6
Data Types and Conversion
7
Variable Assignment and Object Storage
8
Immutability and Operators
9
Conditional Statements and Loops
10
Quiz-1: Data Types
11
Assignment-1: Operators | Loops
12
Quiz-2: Conditionals
13
Conditional Statement and Loops Practice
14
Python Loops
15
While Loops
16
Strings
17
Strings Lists and Tuples
18
Quiz-3: Loops | Strings
19
Lists , Tuples and Dictionaries
20
Assignment-2: List | Tuples | Dictionaries
21
Quiz-4: List | Tuple
22
Lists and Tuples
23
Dict | Set
24
Function
25
Modules and Packages – 1
26
Modules and Packages – 2
27
Quiz-5: Dict | Set
28
File Handling
29
Assignment-3: Functions | Modules
30
Quiz-6: Functions
31
File Handling Regular Expression
32
Regular Expression – 1
33
Regular Expression – 2
34
Functional Programming – Map filter lambda
35
Quiz-7: File Handling | Regular Expressions
36
Lambda functions and List Comprehensions
37
Assignment-4: Map | Filter | Lambda
38
Quiz-8: Python Concepts
39
Problem Solving | Doubts Clearning
40
Object Oriented Programming-1
41
Object Oriented Programming – 2
42
Quiz-9: Regular Expressions
43
Object Oriented Programming-3
44
Assignment-5: OOPs
45
Quiz-10: Map | Lambda
46
Object Oriented Programming – 4
47
Object Oriented Programming – 5
48
Unit Testing & Debugging
49
Exception Handling and Generators
50
CSV, JSON, XML File Handling
51
Quiz-11: OOPs
52
Requests & Beautiful Soup
53
Final Project
54
Assignment-6: JSON and OOP Assignment
55
Quiz-12: Testing | Error Handling
56
Collections and Datetime
DSA Basic
1
DSA Intro | Arrays
2
Stacks
3
Queues
4
Linked List
5
Quiz-1: Basic Operations
6
Problem Solving Session
7
Assignment-1: Linear Data Structures
8
Quiz-2: Linear Data Structures
9
Doubt Clearing Session
10
Time Complexity
Python Certification Preparation
1
Quiz 1: Data Types
2
Quiz 2: Operators in Python
3
Quiz 3: Conditional Statements
4
Quiz 4: Looping Statements
5
Quiz 5: Functions
6
Assignment 1 : Hackerrank
7
Assignment – 2 : Hackerrank
8
Quiz 6: Map Filter and Lambda
9
Quiz 7: List Comprehension
10
Assignment 3 : Hackerrank
11
Quiz 8: Object Oriented Programming Basics-1
12
Quiz 9: Object Oriented Programming Basics-2
13
Quiz 10: Iterators, Generators, and Itertools
14
Assignment 4 : Hackerrank Questions
15
Assignment 5 : Interview Questions
16
Quiz 11: Object Oriented Programming Inheritance
17
Quiz 12: Object Oriented Programming Polymorphism
18
Quiz 13: Object Oriented Programming Operator Overloading
19
Live Project: Movie Ticket Booking System Replica
20
Assignment 6 : HackerRank Questions
21
Quiz 14: File Handling
22
Quiz 15: JSON XML and CSV files
23
Quiz 16: Data Types: Lists
24
Quiz 17: Data Types : Strings
25
Quiz 18: Data Types: Dictionary
26
Live Project: Food Delivery App Replica
27
Mini Project (12 Hours Drill)
28
Live Project: library management system
29
Demo Exam Project Building | Doubt Clarification
MySQL
1
Database Fundamentals
2
Tables | Queries
3
SQL Queries | JOIN
4
Quiz-1: DBMS and Tables
5
MySQL – Query Practice and Revision
6
Assignment – 1
7
Quiz-2: DBMS and Queries
8
Views | Normalization
9
Normalization | ER diagram
10
Quiz-3: Databases
11
MySQL Revision and Interview questions
12
SQL Functions | Stored Procedure
13
Interview Preparation Part 1
14
Interview Preparation part 2
Data Analysis Fundamentals
1
Career Overview – Data Scientist
2
Understanding of Data
3
Quiz-1: Intro to Data
4
Understanding Data Operations
5
Assignment-1: Create New Conditional Column
6
Data Modeling
7
Quiz-2: Excel
8
Excel Refresher
9
Data Quality
10
Power Query for Data Analysis
11
Quiz-3: Data Quality
12
PowerQuery Essentials – I
13
Quiz-4: Power Query
14
PowerQuery Essentials – II
15
Practice Problems | Doubts Clearing
16
Data Visualization – Introduction
17
Power BI Essentials – I
18
Power BI Essentials – II
19
Quiz-5: Data Visualization
20
Quiz-6: Power BI
21
Power BI Essentials – III
22
Refresher Session
Data Wrangling & Visualization
1
Introduction to Data Wrangling
2
Understanding NumPy Fundamentals using Image
3
Getting deep with NumPy Utilities
4
Quiz-1: NumPy
5
Introduction to Pandas & Common Utilities
6
Assignment-1: NumPy
7
Quiz-2: NumPy
8
Practice Problems | Doubts Clearing
9
Assignment Discussion
10
Data Analysis, Manipulation & Cleaning using Pandas
11
Data Visualization using Seaborn
12
Quiz-3: Pandas
13
More Case Studies for Interviews
14
Assignment-2: Pandas
15
Quiz-4: Pandas
16
Doubt Clarification Session Including Python
17
NumPy Revision
18
Data Transformation using Pandas – 1
19
Data Transformation using Pandas – 2
20
Quiz-5: Pandas
21
Data Transformation using Pandas – 3
22
Final Project: Data Wrangling
23
Quiz-6: Seaborn
24
Data Transformation using Pandas – 4
25
Practice Problems | Doubt Clarification
Machine Learning
1
Introduction to Machine Learning
2
Nearest Neighbours & Distance Vectors
3
Understanding Metrices & Implement NN using NumPy
4
Quiz-1: Introduction to ML
5
Quiz-2: Nearest Neighbours
6
Regression in NN & Common Datasets
7
Assignment-1: Nearest Neighbours & KMeans
8
Unsupervised Learning using KMeans
9
Data Preprocessing for Machine Learning
10
Using Preprocessing in ML Applications
11
Introduction to Linear Models
12
Quiz-3: Data Preprocessing Basics
13
implement Linear Regressions & Gradient Descent
14
Assignment-2: Problems using Data Preprocessing
15
Quiz-4: Linear Models
16
Using Linear Regression in Applications
17
Bias & Variance
18
Logistic Regression
19
Assignment-3: Linear Models
20
Quiz-5: Linear & Logistic Regression
21
Cross Validation and Hyper Parameter
22
Quiz-6: Cross Validation & Colum Tranformer
23
Pipeline & ColumnTransformer for ML Model
24
Case Studies for Bias, Variance, Validation and Hyper-parameters
25
Dealing Heterogenous Data
26
Fundamentals of Decision Tree
27
Quiz-7: Pipelines & Hyper-parameter Tuning
28
Understand Decision Tree Algorithm
29
Quiz-8: Decision Trees
30
Implement Regression and Classification DC in Python
31
Support Vector Machines
32
Natural Language Processing
33
Text Preprocessing
34
Conditional Probability & Bayes Theorem
35
Types of Naive Bayes & Applications
36
Assignment Discussion
37
Assignment-4: Decision Tree
38
Case Studies: NLP
39
Assignment-5: Naive Bayes
40
Quiz 9 : NLP & Text Preprocessing
41
Dimensionality Reduction
42
Assignment-6: Machine Learning on Text
43
Revision Session
44
Feature Extraction
45
Quiz 10 : Conditional Probability & Bayes’ Theorem
46
Handling of Outliers and imbalanced classes
47
Quiz-11: Dimesionality Reduction & Feature Extraction
48
Quiz-12: Ensemble Models
49
Ensemble Models
50
CNN for Image Classification
51
Discussion Session
52
Introduction To ANN
53
Overview Session
54
Implementation Of ANN
55
Introduction To CNN
56
Implementation Of CNN
DSA Advanced
1
Searching and Sorting
2
Assignment-1: Linear Data Structures
3
Quiz-1: Searching
4
Assignment-2: Searching & Sorting
5
Quiz-2: Sorting
6
Sorting | Recursion
7
Assignment-3: Trees
8
Trees
9
Quiz-3: Trees
10
Graphs
11
Quiz-4: Graphs
12
Assignment-4: Graphs
13
Doubt Clarification Session
This program is for you if you want to work as a Data Scientist. You can join the program whether you are a fresh graduate, or you want to change your domain. We believe you have the right to choose a career path of your choice.
Our career development team will help you prepare resume, take mock interviews and get you ready for the hiring day. We will also connect you to our hiring partners but before we do that you will have to clear our assessment to ensure that you are ready for the job.
After the completion of the program, we assess you to ensure that you are job-ready. If you clear the assessment, you will get an ISIT Graduation Certificate. Our program graduation certificate holds high value amongst our hiring partners, so you will get a priority over other applicants.
The duration for the program is almost 30 weeks.
No, the entire program is online including the live sessions, quizzes, project submissions and placements.
You need to have a laptop/desktop with a minimum configuration of 1GHz Processor, 4GB RAM, 120GB Hard Disc, Mic, Internet Connection (in case you are taking online sessions)
Yes, we will connect you to job opportunities through our employer network in India.
Boost your career opportunities by developing relevant skillsData Science and AI Master Program With Unlimited Interview CallsA complete guide with real-life exercises & domain oriented approach.
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