Data Science - ML - AI - Big Data with Cloud & Tableau
Python, Hadoop, Spark, Data Analytics, Linear Algebra, Statistics, Probability Concepts, Machine Learning, Deep Learning, Data Science, Artificial Intelligence, Tableau, AWS Cloud.
Course contents for Data Science - ML - AI - Big Data with Cloud & Tableau Training in Kochi, Kerala.
Course Contents :
- Big Data Analytics (Hadoop & Spark)
- Python & Advanced Python
- Exploratory Data Analytics
- Maths for Data Science
- Data Science with AI- Python
- Machine Learning - Python
- Deep Learning - Python
- Tableau Visualisation
⏰ Duration: 6 Months, 6 Days a Week, 2-3 Hours/day
📅 Next Batch : May 19th 2021
👨🎓 For admissions: Click to Enroll
Detailed Syllabus
Apache Hadoop
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
Apache Spark
Python, Introduction to PySpark, Spark Basics, Spark Installation, Spark RDDs & Pair RDDs, Spark Application Deployment, Parallel Processing, Spark SQL, Spark Data Frames, Spark Advanced Concepts, Spark Project.
AWS CLOUD
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, Functional Programming, Map, Reduce, Filter, Iter tools, Python to DB.
Mathematics for Data Science
Linear Algebra:
Vector spaces, subspaces, span, basis and dimension,
Matrices and linear transformations- Linear map as a matrix, rank and nullity of a matrix, matrix multiplication, inverse and transpose, eigen values, eigen vectors
Introductory statistics:
Mean, median, mode, variance and standard deviation, co-variance and correlation
Probability concepts:
Permutations and combinations, unions and intersections, random experiment, sample space, events, probability axioms, conditional probability, Bayes’ theorem, random variables,
Discrete and continuous distributions-Uniform, Binomial, Poisson and Normal distributions
(sampling, central limit theorem)
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, Object Detection, 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.
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.
How We Can Help You
Data Science is undoubtedly one of the most interesting and highly rewarding career options in today’s digitally competitive era. As the demand for data science professionals is expected to grow, pursuing a career in the field is sure to help young and aspiring candidates to meet all their career-related goals. Finding a reputed institute is the best step of the journey, and this is where Luminar Technolab can be of great help to you.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.
Why Luminar Technolab
