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Cohort 111 - Evening - (DA/DS - SB)
Link, Passcode & Updates Section
Batch 111 - Link & Passcode.
High level overview of data science, business intelligence, analytics and data engineering with real world examples
20th October Recording (155:56)
20th October File
Statistics overview and descriptive statistics.
26 October recording (152:49)
26th October File
Moments of Statistics, measures of spread, shape and errors of data.
27th October Recording (153:54)
27th October File
1. Function & it's type 2. Lambda Function 3. Module-Math ,Random 4. Exceptional Error handling
9th November Recording (154:21)
9th November File
1.Pandas Library --Series, Dataframe, Basics of Statistics
10th November Recording (154:52)
10th November File
Basics of Programming and python
16th November Recording (154:47)
16th November File
Python data structures, functions
23rd November Recording (151:33)
23rd November File
Basic concepts of pandas and numpy along with their functions
24th November Recording (152:12)
24th November File
Basics of Excel, Excel functions and Pivot Table
30th November Recording (150:19)
Advanced excel and statistics using excel
1st December Recording (151:21)
30th November and 1st December File
Databases, SQL, SQL syntax and logic building
7th December Recording (153:21)
Hands on practice of SQL and introduction to data visualization
8th December Recording (152:17)
Files
Data Visualization and Power BI - Introduction to data visualization and Power BI feature
21st December Recording (150:11)
file
Report Visualization and properties - Hands on practice Report Visualization
22nd December Recording (147:55)
file
Hierarchies and drill down reports - Hierarchies and Drill down reports in Power BI
28th December recording (203:06)
files
DAX expressions - DAX expressions in power bi
29th December Recording (148:06)
files
PowerBI deployment and cloud usage
4 january recording (133:30)
File
Data Wrangling, data cleaning and EDA
5th January recording - part 1 (48:04)
5th January recording - part 1 (102:14)
Files
Statistical analysis using visualization in Python
11th January Recording (154:20)
File
Supervised Machine Learning and Linear Regression
12th January Recording (165:09)
Files
Google Collab Links
Theoretical Explanation of Linear regression
18th January Recording (158:52)
File
Explanation of Logistic Regression
19th January Recording (151:46)
File
Assignment
KNN, Decision Trees
25th January Recording (154:01)
File
Decision Trees, Random Forest and KNN
1st February recording (150:51)
Practical: Decision Trees, Random Forest and KNN
2nd February recording (150:27)
files for 1st and 2nd february
K Means Algorithm, Hierarchal Clustering
8th February Recording (149:19)
Practical and theory: NLP
9th February Recording (150:58)
8th and 9th February Files
Basics of Deep Learning, Intro to AI and Cloud Computing
15th February Recording (151:38)
Artificial Neural Network
16th February Recording (150:40)
Files
ANN, Optimizers and Cost functions
22nd February Recording (147:06)
File
Practice module for Deep Learning with Keras
1st March Recording (150:26)
File
Mask Detection project
2nd March Recording (151:06)
File
Object detection using Yolo, OpenCV
8th March Recording (150:48)
Multiple object Detection using Yolo, OpenCV, Intro to Google Colab
15th March Recording (148:49)
Files
Introduction to cloud computing
16th March Recording (148:56)
Files
New section
22nd March Recording (150:11)
New section
23rd March Recording (155:08)
29th March Recording
29th March Recording (150:30)
New section
30th March Recording (149:46)
files for 1st and 2nd february
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