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Cohort 131 - (Da/Ds/GenAI - DD)
Course content
44 sections | 91 lessons
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Cohort 131 - Link & Passcode , Update section
1 Lessons
Data Analytics basics, scope, application
2 Lessons
Components of DS, Big Data, Fundamentals of Data
2 Lessons
EXCEL FUNCTIONS
2 Lessons
Data Analysis, Correlation, Regression, Co-variance, What-If Analysis, Goal Seek, Pivot Query, Loading Data, Transformations, Live Data Connection and Analysis.EXCEL PIVOT TABLE ,Sum-if & ifs, Average-if & ifs, Count-if & ifs, Lookup Function - VLOOKUP, HLOOKUP, XLOOKUP, Excel Shortcuts
2 Lessons
VLOOKUP,HLOOKUP, Moving Average.Descriptive Stats Regression. Overview of Data.Types and Forms of Data. Applications and E.g of Data.Overview of Statistics.Types of Statistics-Applications and E.g.DESCRIPTIVE STATISTICS. Functions in Descriptive Statistics-Applications and Its Mathematical
2 Lessons
Co-efficient Of Variation I. Correlation i. Pearson ii. Spearman j. Co-variance k. Squared Error, Mean Squared Error, RMSE, MAD
1 Lessons
INFERENTIAL STATISTICS a. Overview of Inferential Statistics b. Population and Sample c. Test in Inferential Statistics d. T-test e. Chi-square f. Anova g. P-value h. Tables and Critical value I. Confidence Interval
2 Lessons
What is Probability Distribution? b. Examples and Applications of Probability Distribution c. What are Normal Distributions? d. What are Uniform Distributions? e. What are Skewed Distributions
2 Lessons
OPERATORS IN PYTHON a. Arithmetic Operators b. Logical Operators c. Membership operators d. Equality Operators e. Comparison Operators
2 Lessons
Data Types : String, List
2 Lessons
DATA STRUCTURE IN PYTHON a. Lists b. Tuple c. Sets d. Dictionary e. Range
1 Lessons
CONTROL FLOW a. If b. If...... elseif c. Loops d. For Loop f. While Loop g. Transfer Statements h. Break I. Continue. j. Pass
2 Lessons
numpy and its operations
1 Lessons
Pandas introduction
2 Lessons
Pandas and Data Visualization basics
1 Lessons
ct: Data Visualization advanced
2 Lessons
EDA in details
1 Lessons
workbench installation, SQL DDL and DML (basic Commands)
2 Lessons
Order By, Distinct. h.Where Clause, Comparison Operators, NULL. I.Logic Operators j.Aggregate Functions: COUNT,MIN,MAX,AVG,SU k.Group By. L.Join and Natural Joi m.Subqueries/Nested Queries/Inner Queries. n.DML: INSERT. o.DML:UPDATE,DELETE. p.DML: CREATE,TABLE. q.DDL: DROP TABLE,TRUNCATE,DELETE.
1 Lessons
SUM ii. MAX iii. Average iv. Rank v. Partition vi. Order by u. Views, Stored Procedures and Tables in MYSQL
2 Lessons
Normalisation, Dimensional Modelling, Data Analysis and Data Wrangling In MYSQL, Database Administration
2 Lessons
MACHINE LEARNING FUNDAMENTALS a. What is ML? b. Different types of ML? c. Life Cycle of ML? d. Challenges of ML?
2 Lessons
ML, Supervised Learning
1 Lessons
Linear regression, L1, L2 regularization, Ridge and Lasso regression.
2 Lessons
logistic Regression, Multiclass, binomial
1 Lessons
Decision Tree, Pruning, Random Forest in Classification and regression
2 Lessons
KNN, Naive Bayes ALgo
1 Lessons
Unsupervised Algo, K mean clustering with example
2 Lessons
Hierarchical clustering, NLP, text Prepocessing
1 Lessons
NLP, POS, Chunking
2 Lessons
NLP
1 Lessons
Neural Network, ANN
2 Lessons
Power BI
2 Lessons
DAX Expression in Power BI and Streamlit
2 Lessons
SDLC, Streamlit, INTRODUCTION TO AI AND CLOUD COMPUTING, Model Deployment, POWERBI DEPLOYMENT & CLOUD - THEORY
1 Lessons
DAX Expression Level 2, Github, Capstone Project
2 Lessons
Generative AI Session
4 Lessons
26th January
2 Lessons
27th January
2 Lessons
28th January
3 Lessons
Further Placement Assistance
1 Lessons
Career Building Session
2 Lessons
Resumes building and Sample Interview Questions
16 Lessons
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