Job Acceleration Program (JAP) |
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Knowing JAP |
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00:00:00 |
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Elaborating JAP |
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00:00:00 |
Chalo INDIA Startup Drive |
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All about Chalo India Startup Drive |
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00:00:00 |
Introduction |
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Data and its importance |
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00:00:00 |
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What is data science? |
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00:00:00 |
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Prerequisites of data science |
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00:00:00 |
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Life cycle of data science? |
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Roles and skills needed in data science |
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PYTHON- Programming language |
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Why python for data science & introduction to python language? |
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00:00:00 |
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Python Install and setup and introduction to IDE ,Google Colab |
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00:00:00 |
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Overview into Data Structures like list, tuple, set, dict, Series, Data Frame, Array |
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00:00:00 |
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Operator |
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00:00:00 |
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Practice on List, Tuple, Set, Dict, Series, Data Frame & Array |
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00:00:00 |
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Slicing and casting |
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00:00:00 |
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If , Else |
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00:00:00 |
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Functions. Lambda Function |
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00:00:00 |
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For Loop, While Loop, |
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00:00:00 |
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Introduction to OOPS, |
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00:00:00 |
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OOPs vs POP, Types of OOPs, |
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00:00:00 |
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Practical Implementation of OOPS |
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00:00:00 |
Data science Library |
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Ai vs Ds vs Ml Vs Dl vs NLP vs CV |
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00:00:00 |
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Use of libraries & libraries in data science |
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00:00:00 |
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Introduction to Pandas and Basic Pandas Commands |
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00:00:00 |
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Pandas Practice |
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00:00:00 |
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Numpy Commands |
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00:00:00 |
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Data Visualization Theory |
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00:00:00 |
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Practice on Data Visualization with Matplotlib |
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00:00:00 |
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Practice on Data Visualization with Seaborn & Plotly. |
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00:00:00 |
Statistics |
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What is statistics? |
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00:00:00 |
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Where to use it in ML? |
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00:00:00 |
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Data and its properties. |
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00:00:00 |
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Different types of analytics |
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00:00:00 |
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Random variables and its types |
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00:00:00 |
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Population vs sample |
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00:00:00 |
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Central limit theorem- Mean median mode |
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00:00:00 |
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Gaussian distribution/Normal distribution |
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00:00:00 |
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Left & Right skewed distribution, kurtosis |
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00:00:00 |
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Use case of Distribution. |
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00:00:00 |
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Hypothesis Testing, |
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00:00:00 |
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Statistical Testing using ANOVA, T-test, 2 Sample, P-Value, Chi-Square Test, F-Statistics, |
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00:00:00 |
Machine Learning |
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Types of machine learning |
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00:00:00 |
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Linear regression theory |
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00:00:00 |
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Overfitting, Underfitting, Generalized model |
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00:00:00 |
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Ridge & Lasso theory |
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00:00:00 |
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Logistic regression theory |
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00:00:00 |
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-Code practice |
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00:00:00 |
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SVM theory |
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00:00:00 |
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-Code project |
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00:00:00 |
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KNN theory |
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00:00:00 |
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K means |
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00:00:00 |
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Hierarchical |
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DBSCAN |
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00:00:00 |
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Naive Bayes theory |
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00:00:00 |
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Code practice |
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00:00:00 |
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Code Practice 1 |
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00:00:00 |
Machine Learning Part-2 |
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Decision Tree theory |
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00:00:00 |
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Decision Tree Part 2 |
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00:00:00 |
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Random Forest |
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00:00:00 |
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ADABOOST |
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00:00:00 |
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Gradient boosting |
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00:00:00 |
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Code Practice 2 |
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00:00:00 |
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classification- recall, precision, F1 score,Confusion matrix, Accuracy |
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00:00:00 |
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regression-MSE,MAE,RMSE,RMLE, R squared,R2 squared |
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00:00:00 |
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XG boost |
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00:00:00 |
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XG boost code practice |
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00:00:00 |
Data preprocessing |
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What is data preprocessing and why it is important |
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00:00:00 |
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Outlier detection , removal and replace. |
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00:00:00 |
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Null and NaN value removal and replace. |
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00:00:00 |
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What is feature Engineering |
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00:00:00 |
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Encoding Techniques part 1 |
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00:00:00 |
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Encoding Technique Part 2 |
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00:00:00 |
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Quiz -4 |
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00:10:00 |
Data preprocessing part-2 |
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Feature Scaling |
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00:00:00 |
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Feature Selection |
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00:00:00 |
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Feature selection part -2 |
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00:00:00 |
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What is imbalance data, and its impacts,Why data balance is important |
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00:00:00 |
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Handling imbalance data. |
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00:00:00 |
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What and Why tuning is important |
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00:00:00 |
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Hyperparameter steps with Sklearn |
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00:00:00 |
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ML model saving , predticing and retraining |
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00:00:00 |
EDA |
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What is EDA, EDA before and after |
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00:00:00 |
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Why automation is need in EDA, Use of automation |
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00:00:00 |
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Mito |
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00:00:00 |
Statistics part-2 |
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Finding outliers in dataset using Z score & IQR |
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00:00:00 |
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5 number summary – IQR |
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00:00:00 |
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Pearson correlation coefficient |
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00:00:00 |
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Confidence Interval, Estimates |
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00:00:00 |
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Kernal density estimation |
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00:00:00 |
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Q – Q plot |
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00:00:00 |
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Box cox transform |
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00:00:00 |
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Permutation, combination |
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00:00:00 |
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Quiz 3 |
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00:08:00 |
Web application |
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Introduction to VScode |
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00:00:00 |
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Use of VScode in Data Science |
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00:00:00 |
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Why is a Web application needed? |
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00:00:00 |
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Approach in making web application? |
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00:00:00 |
FLask(one on one) |
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Introduction to Flask |
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00:00:00 |
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HTML, CSS basics |
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00:00:00 |
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Flask Framework and Syntax |
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00:00:00 |
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Flask Framework and Syntax part-2 |
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00:00:00 |
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Introduction to Git |
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00:00:00 |
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Use of Git |
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00:00:00 |
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Introduction to Heroku |
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00:00:00 |
Flask (bulk prediction) |
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flask bulk prediction |
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00:00:00 |
Streamlit(bulk prediction) |
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Introduction to streamlit |
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00:00:00 |
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Streamlit use case and Syntax |
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00:00:00 |
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-Deployment to streamlit |
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00:00:00 |
Streamlit (one on one) |
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streamlit one on one predition |
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00:00:00 |
Django(one on one) |
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Intro to django |
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00:00:00 |
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Django Syntex and advantages |
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00:00:00 |
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django deployment in heroku |
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00:00:00 |
django (bulk prediciton) |
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django bulk prediction |
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00:00:00 |
AWS |
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Introduction to AWS |
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00:00:00 |
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Deployment to AWS |
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00:00:00 |
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Django deployment in Aws |
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00:00:00 |
SQl |
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wha is database, sql vs nosql |
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00:00:00 |
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flask database |
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00:00:00 |
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django database |
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00:00:00 |
MongoDB |
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MongoDB |
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00:00:00 |
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MongoDB in flask |
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00:00:00 |
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Quiz 2 |
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00:10:00 |
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MongoDB in Django |
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00:00:00 |
Deep learning |
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Deep learning Introduction |
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00:00:00 |
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Difference between Deep learning and machine learning |
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00:00:00 |
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ANN |
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00:00:00 |
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ANN part-2 |
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00:00:00 |
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ANN part-3 |
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00:00:00 |
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Code Practice 3 |
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00:00:00 |
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CNN |
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00:00:00 |
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CNN part -2 |
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00:00:00 |
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CNN part -3 |
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00:00:00 |
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RNN |
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00:00:00 |
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RNN part -2 |
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00:00:00 |
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RNN part -3 |
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00:00:00 |
NLP |
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Nlp basics and working principle |
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00:00:00 |
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NLTK |
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00:00:00 |
Time Series |
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What is Time Series |
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00:00:00 |
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Time series code practice |
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00:00:00 |
Machine Learning Project |
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machine learning projects part-1 |
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00:00:00 |
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machine learning projects part-2 |
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00:00:00 |
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deep learning projects part-1 |
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00:00:00 |
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deep learning projects part-2 |
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00:00:00 |
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NLP learning projects part-1 |
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00:00:00 |
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Time series projects part -1 |
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00:00:00 |
MLOps |
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What is Mlops |
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00:00:00 |
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Use of Mlops |
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00:00:00 |
HADOOP |
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Introduction to HADOOP |
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00:00:00 |
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HADOOP Distributed File System |
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00:00:00 |
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HADOOP Yarn |
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00:00:00 |
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Hadoop- MapReduce Practical Assignments |
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00:00:00 |
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Hadoop MapReduce |
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00:00:00 |
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Hadoop Installation and Map Reduce Job Execution DEMO |
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00:00:00 |
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Step by Step Guide : Hadoop 3.3.0 installation and MapReduce Job Execution on Windows |
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00:00:00 |
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Step by step Guide Ubuntu (Linux) virtual machine installation on windows and configure Hadoop |
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00:00:00 |
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Map Reduce – Test your Knowledge |
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00:03:00 |
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Hadoop Introduction Quiz |
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00:02:00 |
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SQL-Structured Query Language |
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00:00:00 |
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Apache HIVE ā Hadoop Ecosystem Tool |
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00:00:00 |
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Step by Step Guide : Apache HIVE installation using Cygwin on Windows & External Table Creation |
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00:00:00 |
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Apache HIVE-Practical Assignment -Part 1 |
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00:00:00 |
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Apache HIVE-Practical Assignment -Part 1-Continued |
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00:00:00 |
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Apache HBase -Hadoop Ecosystem Tool |
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00:00:00 |
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Step by Step Guide : Apache Hbase installation on Windows & Table Creation |
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00:00:00 |
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Apache HBase Practical Assignment |
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00:00:00 |
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Hadoop Eco System- Other Tools |
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00:00:00 |
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Hadoop ā Test your knowledge |
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00:04:00 |
Spark |
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Apache Spark -Session |
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00:00:00 |
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Apache Spark Programming Guide |
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00:00:00 |
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Apache Kafka Stream processing and DEMO |
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00:00:00 |
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Apache Spark Streaming |
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00:00:00 |
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Python for Apache Spark ļæ½ļæ½ļæ½ pySpark |
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00:00:00 |
Getting into Azure |
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Big Data and Cloud Computing |
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00:00:00 |
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Microsoft Azure Fundamentals and Overview |
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00:00:00 |
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How to Create a New Microsoft Azure Account |
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00:00:00 |
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Azure Subscription Policies ,Resource Groups and Storage Account |
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QUIZ – 5 |
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00:10:00 |
Starting with Azure |
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Microsoft Azure- Working with Data Storage |
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00:00:00 |
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Microsoft Azure ā DataBricks |
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Microsoft Azure- Working with Databricks |
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00:00:00 |
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Microsoft Azure- Cosmos DB |
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00:00:00 |
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Microsoft Azure SQL |
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00:00:00 |
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Microsoft Azure Synapse Analytics and PolyBase |
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00:00:00 |
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Microsoft Azure Stream Analytics and event hubs |
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00:00:00 |
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Microsoft Azure Data Factory Service ļæ½ļæ½ļæ½ ADF |
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00:00:00 |
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Microsoft Azure Creating a Virtual Machine |
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00:00:00 |
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Microsoft Azure ļæ½ļæ½ļæ½ Monitoring and Troubleshooting Data Storage and Processing |
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00:00:00 |
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Microsoft Azure : Data Engineer Associate Certification Path- Part 1 |
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00:00:00 |
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Microsoft Azure : Data Engineer Associate Certification Path- Part 2 |
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00:00:00 |
QUIZ SECTION |
Bonus Section |
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FINAL TEST |
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Unlimited |
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Congrats ! Submit the course completion form. |
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