Python, Hadoop, Spark, Data Analytics, Machine Learning, Deep Learning, Data Science, Artificial Intelligence, Tableau, AWS Cloud.
Course contents for Big Data - Data Science - Machine Learning - Deep Learning (AI)Training in Kochi, Kerala.
Course Contents :
1. Big Data Analytics (Hadoop & Spark)
2. Python & Advanced Python
3. Data Analytics
4. Maths for Data Science
5. Data Science with AI- Python
6. Machine Learning - Python
7. Deep Learning - Python
⏰ Duration: 5 Months, 6 Days a Week, 2-3 Hours/day
Python, Unix commands, SQL, Apache Maven, IntelliJ IDE, Git, Bash script, AWS EMR, Big Data Analytics, Cloudera Hadoop, Hadoop Architecture, Hadoop Installation Mode and HDFS, Hadoop Clustering, Map Reduce (Version 1 & 2), YARN Application, SQL, Pig, Sqoop, Hive, HBase, Project
Python, Introduction to PySpark, Spark Basics, Spark Installation, Spark RDDs & Pair RDDs, Spark Application Deployment, Parallel Processing, Spark SQL, Spark - MLlib(Machine Learning), KNN, Kmeans, GMM, Naive Bayes, Spark Data Frames, Spark Streaming, Kafka, Spark Advanced Concepts, Spark Project.
Introduction to Amazon Web Services, AWS EC2, AWS EMR, AWS Simple Storage Service (S3)
Python & Advanced Python
Introduction to Python, PyCharm, Language Fundamentals, Conditional Statements, Looping, Control Statements, String Manipulation, Lists, Tuple, Dictionaries, Functions, Modules, Input-output, Exception Handling, OOPS Concepts, Regular Expressions, Multithreading, Functional Programming, Map, Reduce, Filter, Iter tools, Python to DB.
Data Science & ML
A-Z of Python(Core and Advanced), Numpys, Pandas, Data Frame, Sci-kit, Exploratory Data Analytics using Python (EDA), Data Wrangling, Data Visualization, Matplotlib, Seaborn, Machine Learning, Supervised Learning - Regression (Simple Linear Regression, Logistic Regression, Multiple Linear Regression, Polynomial Regression, Decision Tree Regression, Evaluating Regression Model Parameters), Classification ( K Nearest Neighbors ( KNN ), Naive Bayes Classifier, Decision Tree Algorithm, Random Forest Algorithm, SVM), Unsupervised Machine Learning - Introduction To Clustering Algorithms, K-Means Clustering, Elbow Method for the optimal value of k in K-Means, Hierarchical Clustering, Capstone Project, Dimensionality Reduction, Principal Component Analysis.
Deep Learning & AI
Natural Language Processing(NLP), NLTK, Neural Networks, CNN, CNN Alexnet, RNN, LSTM, TFIDF, Keras, Tensorflow, Speech recognition, Transfer Learning, Chatbot, Microsoft bot framework, AI chatbot, Rasa chatbot, Open Computer Vision (OpenCV), Optical Character Recognition (OCR), Capstone Project.
Data Visualization - Tableau
Working with Tableau Public, Connecting Data with Tableau, Relationships in Tableau, Filters in Tableau, Adding Dimensions in Tableau, Granularity in Tableau Analysis and Calculations in Tableau, Plotting in Tableau, Logical Operations on Tableau, Visualisations in Tableau Dashboard and Stories
What is Data Science Eco-System?
The term Data Science is commonly used in the business field, and most of us would have probably heard it at least once. However, it is true that some of us do not know what data science really is. Data science is the creative art or process of blending various tools, machine learning programs, and algorithms. The primary goal of data science is to discover and extract knowledge from structured and unstructured data.
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Why Learn Data Science
A survey conducted by NASSCOM (The National Association of Software and Services Companies) revealed that approximately 1 and a half lakh job positions remain vacant in the field of data science. It is estimated that there will be a deficit in the number of data science professionals by more than 2 lakhs by the end of next year.
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Why Luminar Technolab