Content.txt

1 - Algorithms and Data Structures (Data structures (lists, arrays, linked lists, queues, stack), Recursion, Trees, Maps and Hashing, Binary Search, Sorting Algorithms, Divide & Conquer Algorithms, Randomized Binary Search, K-smallest elements using Heaps, Build Red-Black Tree, Bubble sort, Merge sort, Quick sort, Sorting strings, Linear-time median finding, Greedy Algorithms, Graph Algorithms, Dynamic Programming, Linear Programming etc.)
2 - Machine Learning for Data Science (Linear/Logistic Regression, Classifications, Support Vector Machine, Decision Tree, Random Forest, Unsupervised Learning, Clustering, Naive Bayes, Bayes Theorem, Bayesian Methods, Ensemble Learning, Generative, XGBoost, LightGBM, CatBoost, Neural Networks etc )
3 - Practical Deep Learning 1 - Computer Vision (Neural Networks, Convolutional Neural Networks (CNN), Image Classification, Object Detection, Object Segmentation, Auto-encoder, Generative adversarial network (GAN), Data Augmentation, Hyperparameter Tuning, Transfer Learning, Tensorflow, Tensorflow Serving etc)
4 - Practical Deep Learning 2 - Natural Language Processing (Neural Networks, Word Vectors, Recurrent Neural Networks, Language Models, Long Short­-Term Memory (LSTM), seq2seq models, Attention Mechanism for seq2seq, Transformer Networks and CNNs, Semi-supervised Learning, Transfer Learning etc)
5 - Data Science (Data Analysis/Visualization, Sampling, Distributions, Hypothesis Testing, Model Evaluations, Model Improvements, Modelling, Model Deployment etc)
6 - Big Data (Big Data, Cloud and Machine Learning, Scala (Scala syntax, Operator, Pattern Matching, Trait, OOP, Functional programming, Functional Data Structure, Traverse, Lazy evaluation, Pattern matching, Actors), Hadoop (YARN, HDFS, MapReduce, Hive/ Impala, Install and run Hadoop), Apache Spark (RDD, Transformation, Lambda, Spark programming model, Install and run Spark on local (Interactive Spark-shell, Running spark job on spark), DataFrames, DataSets, Spark SQL, ETL with Spark, AWS, Big Data in AWS, Machine Learning in Big Data, Machine Learning using Spark MLlib)