Advance Data Science with BFSI
Course Instructor
Abhishek Gupta
₹145000.00
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Course Overview
Schedule of Classes
Course Curriculum
2 Subjects
Advance Data Science with BFSI
341 Learning Materials
Python by Instructor 1
1. Induction_class | 21st February 2022 | Monday | 8am to 10am IST
Video
3:01
2. Git & Github | 22nd February 2022 | Tuesday | 8am to 10am IST
Video
2:21:19
3. git class | 23rd February 2022 | Wednesday | 8am to 10am IST
Video
2:13:21
4. Introduction of Python | 24th February 2022 | Thursday | 8am to 10am IST
Video
2:8:38
5. Python Introduction Part 2 | 25th February 2022 | Friday | 8am to 10am IST
Video
2:9:59
6. Memory Management | 1st March 2022 | Tuesday | 8am to 10am IST
Video
2:9:59
7. Python Components | 2nd March 2022 | Wednesday | 8am to 10am IST
Video
2:11:8
8. Operators In Python | 3rd March 2022 | Thursday | 8am to 10am IST
Video
2:21:34
9. Extra_Class | 5th March 2022 | Saturday | 9am to 11am IST
Video
2:22:00
10. String_string_method | 8th March 2022 | Tuesday | 8am to 10am IST
Video
2:11:57
11. String_Methods_conditional_statement | 9th March 2022 | Wednesday | 8am to 10am IST
Video
2:16:54
12. Loops in Python | 10th March 2022 | Thursday | 8am to 10am IST
Video
2:3:14
13. Loop_Practice_List | 11th March 2022 | Friday | 8am to 10am IST
Video
1:44:44
14. List_Method | 14th March 2022 | Monday | 8am to 10am IST
Video
2:26:00
15. Tuple Tuple Method Dictionary | 16th March 2022 | Wednesday | 8am to 10am IST
Video
2:3:47
16. Dictionary Methods Sets | 17th March 2022 | Thursday | 8am to 10am IST
Video
1:57:39
17. Assignment_Revision | 20th March 2022 | Sunday | 9am to 11am IST
Video
1:53:25
18. Set Frozen | 21st March 20222 | Monday | 8am to 10am IST
Video
1:30:35
19. Function in Python | 22nd March 2022| Tuesday | 8am to 10am IST
Video
1:33:18
20. Lambda Function | 23rd March 2022 | Wednesday | 8am to 10am IST
Video
1:25:25
21. Lambda Arguments | 24th March 2022 | Thursday | 8am to 10am IST
Video
2:9:26
22. Recursion Iterator | 28th March 2022 | Monday | 8am to 10am IST
Video
1:40:46
23. File Handling | 29th March 2022 | Tuesday | 8am to 10am IST
Video
2:01
24. Exception Handling Regex | 31st March 2022 | Thursday | 8am to 10am IST
Video
1:52:4
25. Regex | 1st April 2022 | Friday | 8am to 10am IST
Video
1:37:44
26. Numpy Introduction | 4th April 2022 | Monday | 8am to 10am IST
Video
1:53:40
27. Numpy Part -2 | 5th April 2022 | Tuesday | 8am to 10am IST
Video
1:20:28
28. Numpy Part-3 | 7th April 2022 | Thursday | 8am to 10am IST
Video
2:042
29. Pandas | 11th April 2022 | Monday | 8am to 10am IST
Video
1:54:40
30. Pandas Part-1 | 12th April 2022 | Tuesday | 8am to 10am IST
Video
1:18:47
31. Pandas Part-2 | 14th April 2022 | Thursday | 8am to 10am IST
Video
1:48:29
32. Matplotlib | 19th April 2022 | Tuesday | 8 am to 10 am IST
Video
1:48:32
33. Matplotlib Part-2 |20th April 2022 | Wednesday | 8 am to 10 am IST
Video
41:4
Python by Instructor 2
1. Git & GitHub
Video
1:26:6
2. GitHub
Video
1:53:8
Git part-2
Video
1:43:21
Jupiter Intro
Video
1:56:45
Interger Data Types
Video
1:33:36
6. Integer Operator
Video
2:10:45
7.
Video
1:51:32
8. String_Part_2
Video
1:51:32
9. String_Part_3
Video
2:3:21
10. List_Part_2_Tuple_Dic_Intro
Video
1:42:18
11. List_Comprehension_Tuple_Dic
Video
1:58:47
12. Tuple_Dictionary_Part_1
Video
2:13:25
13. Dic_Part_2
Video
1:41:53
14. Conditional Statement
Video
1:21:16
15. Loops
Video
1:58:57
16. Functions
Video
2:34:36
17. Functions_Part_2_Map_reduce_iterator
Video
2:03
18. Global_Local_Variable_enumarate_Iterator_Module
Video
1:55:17
19. File_Handling
Video
1:23:2
20. Exceptional Handling
Video
2:4:12
22. Regex_Part_2
Video
1:44:22
23. Regex_part_3
Video
1:45:27
24. Numpy_Part_1
Video
1:50:38
22. Regex part 1
Video
1:21:20
25. Numpy_Part_2
Video
1:47:18
26. Pandas_Part_1
Video
2:4:3
27. Pandas_Part_2
Video
1:59:13
28. Pandas_Part_3_Matplotlib
Video
1:51:10
29. Matplotlib
Video
1:51:17
30. Seaborn
Video
1:31:13
Python by Instructor 3
1. Git_Hub
Video
2:57:55
2. Git_&_GitHub
Video
2:51:18
3. Operating System
Video
3:021
4. Python_Intro
Video
2:38:54
5. Components in Python
Video
2:45:34
6. Datatypes in Python
Video
2:39:29
7. Operators_in_Python
Video
2:33:11
9. Conditional & Control Statement
Video
2:29:58
8. Operators_part_2 |
Video
2:46:21
10. Conditional & Control Statement
Video
1:56:19
11. Strings
Video
2:45:43
13. List in Python
Video
2:25:13
14. Dictionary in Python
Video
2:29:00
15. Functions_in_Python
Video
2:25:3
16. Functions_in_Python_2
Video
2:18:21
17. Models_in_Python
Video
2:29:49
18. Files in Python - 2
Video
2:20:6
19. Exception_Handling
Video
2:29:13
20. Regular Expression in Python
Video
2:22:17
21. Numpy_Part_1
Video
2:25:36
22. Numpy_2
Video
2:26:52
23. Pandas_Part_1
Video
2:20:24
Pandas_Part_2
Video
2:47:53
Matplotlib_2
Video
2:8:6
Seaborn
Video
3:6:20
Case Study
Video
2:15:42
Statistics & Machine Learning Instructor 1
1. What is Statistics?
Video
2:1:41
2. Descriptive Statistics
Video
2:9:48
3. Variance
Video
2:4:51
4. Z-Score Method
Video
2:8:48
5. Sampling Techniques
Video
2:11:19
6. Probability
Video
2:12:9
7. Bayes Theorem
Video
2:14:29
8. Normal Distribution - Central Limit Theorem
Video
1:41:19
9. Hypothesis
Video
1:51:4
10. T-Test
Video
2:4:25
11. ANOVA
Video
2:5:26
12. Stats Hands On
Video
2:16:14
13. Linear Algebra
Video
2:16:00
14. Machine Learning
Video
2:040
15. Preprocessing
Video
2:04
16. Linear Regression
Video
1:50:9
17. Adjusted R2
Video
2:9:4
18. Logistic Regression
Video
2:5:7
19. Logistic Regression
Video
2:8:26
20. Decision Tree
Video
1:59:14
21. Random Forest
Video
2:24:14
22. K- Nearest Neighbours
Video
2:17:34
23. Naive Bayes
Video
1:49:58
24. Principal Components Analysis
Video
1:5:33
25. SVM
Video
1:36:38
Statistics & Machine Learning Instructor 2
1. Box and Whisker Plots
Video
1:57:13
2. Descriptive Statistics
Video
2:5:25
3. Correlation & Regression
Video
1:59:00
4. Sampling Methods
Video
1:55:27
5. T - Distribution
Video
2:8:50
6. Hypothesis
Video
1:45:25
7. ANOVA- Analysis of Variance
Video
2:10:27
8. Introduction to Probability Deduction
Video
2:1:32
9. Probability Distribution
Video
1:52:6
10. Classification Tree
Video
2:5:10
11. Decision Tree code to built CART Tree
Video
3:53:56
12. Random forest
Video
1:44:16
13. Regression : Predicting House
Video
1:31:37
14. Clustering
Video
1:54:30
15. Support Vector Machines
Video
1:39:20
16. Logistic Regression
Video
1:44:26
17. Nearest Neighbor Classification
Video
1:28:37
18. Bayes Classification
Video
1:21:59
19. Similarity : Retrieving Documents
Video
1:21:11
20. Artificial Neural Network
Video
1:23:22
Statistics & Machine Learning Instructor 3
1. Statistics_Intro
Video
1:30:55
2. Descriptive Statistics
Video
2:52:36
3. Probability
Video
1:55:9
4. Python Naive Bayes
Video
2:40:41
5. Bayes Theorem
Video
2:44:12
6. Probability_Distribution
Video
2:50:10
7. Correlation
Video
2:41:40
8. Interval Estimation
Video
3:3:6
9. Null & Alternative Hypothesis
Video
2:56:18
10. T-Test
Video
2:42:50
11. Machine Learning
Video
2:41:36
12. LR_with_Numpy
Video
2:21:33
13. LR_with_Diabetes_Data
Video
2:58:35
14. Skewness & Kurtosis
Video
2:51:25
15. Machine Learning
Video
2:47:29
16. Preprocessing
Video
2:48:41
17. SVM
Video
2:48:13
18. Clustering Techniques
Video
2:19:18
19. Model Selection & Evaluation
Video
2:46:12
20. Model Selection & Evaluation_2
Video
1:40:8
SQL
SQL Intro
Video
1:54:30
Normilization
Video
1:48:14
Joins
Video
1:40:41
SQL Views
Video
1:48:50
User Defined Functions
Video
1:40:1
Stored Procedures
Video
2:1:21
MongoDB Intro
Video
2:9:39
What is MongoDB
Video
1:29:18
MongoDB CRUD Operations
Video
1:47:32
Indexing
Video
1:46:49
MongoDB Drivers
Video
1:49:10
Sharding MongoDB
Video
1:34:19
Tableau
Tableau Intro
Video
1:54:41
Adding Parameters
Video
1:59:13
Manipulating Graph Size
Video
1:50:52
Funnel Chart
Video
1:48:51
Actions
Video
1:45:2
Viz Animations
Video
1:52:43
Dashboard Actions
Video
1:50:58
Connecting to SQL Server
Video
1:42:47
PowerBi
Slicers in PowerBi
Video
1:46:16
Data Modelling in PowerBi
Video
1:38:29
PowerBi Intro
Video
1:46:46
Tabular data in PowerBi
Video
47:42
Stacked Area Chart in PowerBi
Video
1:44:52
Creating Report in PowerBi
Video
1:49:14
Power Query
Video
1:55:48
Merging Sheets in Power Query
Video
1:55:8
Mackaroo - Random Data Generator
Video
1:10:3
R-Programming
R CLass_Intro
Video
3:26:34
Vector, List, Factor, Conditional Statement
Video
3:16:34
Matrix & Dataframes
Video
3:15:40
Imputing NA Values
Video
3:2:11
Timeseries
Time Series Analytics & Forecasting
Video
1:55:44
Additive Method
Video
1:56:59
End to End Project-Time Series Forecasting
Video
1:53:39
Time Series Class 4 | 27th March 2023 | Monday | 8am to 10am IST
Video
1:48:3
Time Series Class-5 | 28th March 2023 | Tuesday | 8am to 10am IST
Video
1:52:21
MongoDB
MongoDB_Intro
Video
2:57:40
Arrays with MongoDB
Video
3:042
MongoDB Structure
Video
2:57:54
Bigdata
BigData_Intro
Video
3:3:52
Hadoop
Video
3:1:36
Map Reduce
Video
2:51:37
Limitation of Map Reduce
Video
3:8:53
Deployment by Instructor 1
Deployment_Intro
Video
2:055
Deployment of ML Model
Video
1:55:52
Flask
Video
2:2:28
Flask_2
Video
2:2:10
AWS Management
Video
1:19:24
Deployment by Instructor 2
Introduction to Deployment
Video
1:55:27
Model Scoring
Video
1:46:10
Flask
Video
1:55:42
DL & NLP Instructor-1
Deep Learning Intro
Video
1:47:53
History of Neural network &DL
Video
2:15:18
Notation
Video
2:11:21
Back Propogation Algorithm
Video
2:9:42
Vanishing Gradient Problem
Video
2:1:6
Weight Initialization
Video
2:9:20
DNN
Video
1:43:53
Feature Scaling
Video
2:5:10
Batch Normailzation
Video
1:39:32
Optimizer
Video
2:6:33
Nesterov Accelerated Gradient
Video
1:41:42
Optimization Method
Video
2:5:27
Hyper Parameter
Video
2:044
CNN
Video
1:58:57
Regression & Classification
Video
2:6:26
Data Augmentation
Video
2:1:19
CNN vs ANN
Video
1:57:5
Lenet 5 Architecture
Video
1:54:57
Case Study
Video
1:45:33
Transfer Learning
Video
2:3:41
Introduction to NLP
Video
2:2:2
NLP Foundation
Video
1:57:4
Stemming
Video
2:1:31
N-Grams
Video
1:37:16
Project - Spam Message Classification
Video
1:38:54
Extract Text
Video
1:35:29
Word2vec
Video
1:31:18
Advanced Ai
1. Introduction to Deep Learning
Video
1:15:25
2. Machine Learning
Video
1:51:32
3. Regression
Video
1:49:9
4. Artificial Neural Networks
Video
1:56:22
5. Artificial Neural Network_Computer Graphics
Video
1:54:41
6. Backpropagation
Video
2:011
7. Tensorflow_2
Video
1:34:17
8. Keras Simplified
Video
1:55:7
9. Keras_Simplified
Video
1:33:34
10. Convolutional Neural Networks
Video
1:21:33
11. Convolution
Video
1:41:7
12. Convolutional Neural Network
Video
1:47:31
13. CNN Assignment
Video
1:41:21
14. Sequence
Video
1:34:28
15. RNN
Video
1:34:28
16. Auto encoders
Video
1:54:4
17. Intro to Autoencoders
Video
1:43:27
18. Pytorch
Video
1:42:41
19. Traffic sign recognition
Video
1:31:45
20. Logistic Regression
Video
1:58:42
21. Adaptive Gradient
Video
1:41:34
22. Transfer Learning
Video
1:48:8
NLP by Instructor 1
NLP
Video
1:57:49
Text Preprocessing
Video
1:53:2
Word Embeddings
Video
1:32:27
Naive Bayes
Video
2:037
Similariry in Text
Video
1:57:9
Information Retrieval
Video
1:55:35
Spacy
Video
1:19:28
Advanced Excel Course
Class_01
Video
2:5:13
Class_02
Video
2:7:12
Class_03
Video
2:6:50
Class_04
Video
2:1:15
Class_05
Video
2:3:50
Class_06
Video
2:4:30
Class_07
Video
2:9:46
Class_08
Video
2:8:19
Class_09
Video
2:7:51
Class_10
Video
2:1:34
Class_11
Video
2:6:15
Class_12
Video
2:4:35
Class_13
Video
1:50:20
Class_14
Video
1:43:33
Computer Vision
1. Computer_Vision_Intro
Video
1:25:44
2. Edge_Detection
Video
1:27:27
3. Moving_Average
Video
1:44:15
4. Dog_breed_identification_Solution
Video
1:45:23
5. Gaussian_Blur
Video
1:46:48
6. Object_Detection
Video
1:27:29
7. Image_Segmentation
Video
1:41:52
8. Object_Detection_Inference
Video
1:50:39
9. Dataset
Video
1:34:4
Advanced NLP
1. Natural_Language_Pre - Processing
Video
1:19:17
2. Word_Embeddings
Video
1:43:11
3. Word_Embeddings_2
Video
1:37:59
4. Word_Embeddings_Using_Deep_Learning
Video
1:35:2
5. Intro_to_Autoencoders
Video
1:33:30
6. Word Embeddings using Deep Learning
Video
1:23:11
7. Attention_Mechanism
Video
1:27:43
8. Tensor_2_Tensor_Intro
Video
1:41:1
9. Tensorflow_Transformer_en_Spanish
Video
1:34:4
10. BERT_for_Sentiment_Analysis
Video
1:38:7
11. Similarity
Video
1:48:18
12. String Similarity
Video
1:31:17
13. Huggingface_Pytorch_Transformers
Video
1:45:23
14. Summarization using Spacy
Video
1:39:47
15. Web_Scraping
Video
1:12:18
Domain Specialization
E-Commerce_Day-1
Video
2:2:21
E-Commerce_Day-2
Video
2:5:23
E-Commerce_Day-3
Video
2:6:35
Banking Domain Day-1
Video
1:34:44
Banking Domain_Day-2
Video
1:44:32
Banking Domain_Day-3
Video
1:29:17
Banking Domain_Day-4
Video
1:40:10
Retail Domain_Day-1
Video
50:54
Retail Domain_Day-2
Video
1:1:59
Retail Domain_Day-3
Video
1:3:25
E-Commerce_Day-1
Video
2:2:21
E-Commerce_Day-2
Video
2:5:23
E-Commerce_Day-3
Video
2:6:34
Supply Chain_Day-1
Video
1:58:48
Supply Chain_Day-2
Video
2:2:3
Finance Domain_Day-1
Video
2:13:58
Finance Domain_Day-2
Video
2:12:40
Text Analysis (Sentiment Classification)
Video
2:4:51
Text Analysis -Day 2
Video
1:55:29
Finance Domain (ATM Transaction)
Video
1:50:26
Finance Domain (ATM Transaction)-2
Video
1:49:24
Data structure and algorithms
1. class -1
Video
1:030
2. Class-2
Video
2:28:26
3. class -3
Video
2:48:8
4. Class -4
Video
3:49:34
5. Class -5
Video
1:54:45
6. Class -6
Video
2:57:11
7. Class -7
Video
2:48:40
8. Class -8
Video
9:39
9. Class -9
Video
3:6:54
10. Class -10
Video
2:13:36
OOPs Class
Class_01
Video
1:45:35
Class_02
Video
1:48:30
Class_03
Video
2:4:21
Class_04
Video
2:12:20
Class_05
Video
1:55:38
Class_06
Video
1:16:47
Resume Session
1. 0-3 yrs of Exp.
Video
1:47:49
2. 8+ Yrs of Exp.
Video
2:025
3. 4 to 8 yrs of Exp.
Video
1:26:22
Adv. Data science with BFSI
1 Learning Materials
content
content
Course Instructor
Abhishek Gupta
715 Courses • 221267 Students
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