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Data Science: Re-defining future value of Actuaries Webinar series 2022-23

About the program

It has been quite some time that, Data Science became a key word in the contour of all professions with Machine learning and Artificial Intelligence as important sub-products. While actuaries traditionally involved in decision making on the basis of Mathematical logics and Statistical inferences, advancement of data science is expected to capture most of the actuarial domain with an impact of multiple disciplines like Mathematics, Statistics, Computer science, information science, Machine learning and Artificial intelligence.

The Data Science and its advancement is going to decide the future values of actuarial profession to a large extent. The Machine learning and Python trainings conducted by the Institute have lifted the confidence and value of many actuarial members who will be in the forefront of re-defining the role of actuaries in finance and risk management. Since Python is largely used in data science as a programming language, a 7.5 hours Python training is also included in this 70 hours training. Those who have already attended both Python and Machine learning webinar series recently conducted by the Institute may find this program as the next level of advanced learning.

Why Actuaries to learn Data Science?

The question as to how fast actuaries to catch up various disciplines of data science to be answered sooner than later for maintaining the unique space and role of actuaries in the market. An actuary with specialisation in data science to remain as an actuary for future;

Program schedule:

Webinars will start on 12 December 2022 which will be spread over 35 sessions of 2 hours each duration. Participants are expected to work on assignments on a regular basis to maintain the continuity of learning and practice.

The program schedule is available in ANNEXURE-I

Recorded videos of all webinars will be made available in the member’s login page until 30 April 2023. However, it is highly recommended to attend all LIVE sessions without fail for optimum learning out of the program.

Registration:

Fee for Students Rupees Six thousand (₹6,000.00) (18% GST extra)
Fee for Associate & Fellow members Rupees Eight thousand (₹8,000.00) (18% GST extra)
For Non-members Rupees Ten thousand (₹10,000.00) (18% GST extra)
Bulk registrations from Employers will be accepted with a minimum registration count of 25, where both members and non-members can together register with a lump sum payment of Rupees Two lakhs (₹200,000.00) only (18% GST extra)
Registration menu Login to IAI >>Training program>>Data Science
Registration opens on On 11 November 2022 6.00PM.
Registration closes on On 10 December 2022 6.00PM.
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Non Member Registration

Faculty

Mr. Vamsidhar Ambatipudi, PGDM (IIMI), FIAI, CERA, FRM, PRM, Associate Professor, BITS Pilani

Coverages :

  • Python
  • Machine Learning
  • Data Visualization
  • Pandas
  • Introduction to Deep Learning
  • Predictive Modelling
  • Math and Stat Principles
  • Time Series Analysis
  • Data Analysis
  • Solutions to Business Problems
  • Introduction to Natural Language processing

Contact :

Point of contact for all related queries: Mr. Ravindra Mastekar at: 022 62433348 or ravindra@actuariesindia.org

ANNEXURE-I

Program Schedule (Tentative)-12 December 2022 to 1 March 2023; 7.00pm-9.00 pm

Sr.

No

Date

Day

Topic

1

12-12-2022

Monday

Introduction to Data Science and Python

2

14-12-2022

Wednesday

Numpy Basic

3

16-12-2022

Friday

Numpy advanced

4

19-12-2022

Monday

Pandas for data manipulation

5

21-12-2022

Wednesday

Essential Math for Data Science

6

23-12-2022

Friday

Data visualization using Matplotlib and Seaborn

7

26-12-2022

Monday

Descriptive Statistics

8

28-12-2022

Wednesday

Inferential Statistics

9

30-12-2022

Friday

Introduction to Machine Learning with essential terminology

10

02-01-2023

Monday

Linear Regression

11

04-01-2023

Wednesday

Exploratory Data Analysis

12

06-01-2023

Friday

Data Cleaning

13

09-01-2023

Monday

Data Pre-processing

14

11-01-2023

Wednesday

Advanced Linear Regression

15

13-01-2023

Friday

Feature Engineering

16

16-01-2023

Monday

Feature Selection

17

18-01-2023

Wednesday

Logistic Regression

18

20-01-2023

Friday

Naive Bayes and KNN

19

23-01-2023

Monday

Decision Trees

20

25-01-2023

Wednesday

Ensembling and Random Forests

21

27-01-2023

Friday

Gradient Boosting

22

30-01-2023

Monday

Challenges in ML

23

01-02-2023

Wednesday

Clustering

24

03-02-2023

Friday

Dimension Reduction

25

06-02-2023

Monday

Time Series 1

26

08-02-2023

Wednesday

Time Series 2

27

10-02-2023

Friday

Natural Language Processing 1

28

13-02-2023

Monday

Natural Language Processing 2

29

15-02-2023

Wednesday

Introduction to recommender systems

30

17-02-2023

Friday

Support Vector Machines

31

20-02-2023

Monday

Artificial Neural Networks

32

22-02-2023

Wednesday

Introduction to Deep Learning 1

33

24-02-2023

Friday

Web scraping

34

27-02-2023

Monday

Working with Databases

35

01-03-2023

Wednesday

Data Science Ethics and way forward