Python, Hadoop, Spark, Data Analytics, Machine Learning, Deep Learning, Data Science, Artificial Intelligence, 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, Spark Advanced Concepts, Spark Project.
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 & Analytics (Python)
Numpys, Understanding the N-dimensional data structure Creating arrays Indexing arrays by slicing or more generally with indices or masks, Basic operations and manipulations on N-dimensional arrays, Plotting with Matplotlib, Accessing Data From Multiple Sources Reading and writing data from local files (.txt, .csv,.xls, .json, etc), Reading data from the database, Scraping tables from web pages (.html), Pandas and data frames, Working with Pandas data structures: Series and DataFrames Accessing your data: indexing, slicing, fancy indexing, Boolean indexing, Data wrangling, including dealing with dates and times and missing data, Adding, dropping, selecting, creating, and combining rows and columns, Data summarization and aggregation methods, Pandas powerful group by method, Reshaping, pivoting, and transforming your data, Seaborn - statistical data visualization, Introduction to Data Analytics using Power BI, Project.
Python - Machine Learning and Deep Learning with AI
Introduction to Python, Jupyter Notebook, Basic Packages, and Data Preprocessing, Pandas and Numpy, Missing Data, Categorical Data, Splitting of Data, Feature Scaling, Regression, Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, Decision Tree Regression, Evaluating Regression Model Parameters, Classification, Logistic Regression, KNN, SVM, Evaluating Classification Model Parameters, Clustering, KMeans Clustering, Hierarchical Clustering, Dimensionality Reduction, Principal Component Analysis, Keras, Tensorflow, CNN, NLP, TFIDF, Computer Vision (Open CV), Optical Character Recognition (OCR), Course Project.
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.
In simple words, a data analyst helps businesses by analyzing data and gives them a clear idea of what is going with their business. Data analysts do not just give you real-time information about your business and insights, instead, they are also able to predict the occurrence of a future event by relying on advanced machine learning tools. This is why the process of data science continues to be integral for startups, small-scale, and large-scale businesses.
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.
However, our country has witnessed an increased demand for data professionals over the last couple of years. The above-mentioned stats clearly indicate that this is the perfect time to attend a big data training course and pursue a career in the field of data science.
The comprehensive data science course that we offer covers a wide range of important Data Science concepts. You can gain proper knowledge of data extraction, data collection, data mining, and data exploration along with advanced topics that cover artificial intelligence and machine learning through our course. The expert team of data science experts at our disposal will ensure a seamless and smooth learning experience for all candidates. Your search for an institute that offers the best data science training in Kochi ends with Luminar Technolab.