After completing this course students will be trained in statistics and machine learning using Python. They will make data driven decisions which provide them a competitive advantage in the market, technologies like Hadoop, Spark, Hive, Machine Learning provides a spring board for AI which makes them ready for Industry 4.0. At the end of the course students will be able to work as Data Analysts, Data Engineers. Studying Big Data will broaden their horizon by surpassing market forecast / predictions for Big Data Analytics
The Post Graduate Diploma in Big Data Analytics (PG-DBDA) is a fulltime post graduate course comprising of 9 Compulsory Modules, aptitude, communication and a Project.
The educational criteria for PG-DBDA course is:
1. Graduate in Engineering (10+2+4 or 10+3+3 years) in IT / Computer Science /
Electronics / Telecommunications / Electrical / Instrumentation. OR
2. MSc/MS (10+2+3+2 years) in Computer Science, IT, Electronics. OR
3. Graduate in any discipline of Engineering, OR
4. Post Graduate Degree in Management with corresponding basic degree in Computer
Science, IT,
Computer Application OR
5. Post Graduate Degree in Mathematics / Statistics / Physics OR
6. MCA, MCM
7. The candidates must have secured a minimum of 55% marks in their qualifying
examination.
C-DAC's application form is common to Post Graduate Diploma in Big Data Analytics (PG-DBDA) Application forms for all the courses are to be filled online at http://acts.cdac.in (recommended).
Course Category |
C-CAT Paper(s) |
Examination fee |
I |
A |
Rs. 1350/- |
II |
A+B |
Rs. 1550/- |
III |
A+B+C |
Rs.1750/- |
After filling the online C-CAT application form, the
examination fee may be paid online through the ‘Make Payment’ step on the main menu
of the online application. No cheque or demand draft (DD) will be accepted towards
payment of C-CAT examination fee.
Online: The examination fee can be paid using credit/debit cards and net banking
through the payment gateway that will be opened upon clicking the 'Online' option of
the 'Make Payment' step. Candidates are advised to follow the instructions/steps
given on the payment gateway, and also print/keep the transaction details for their
records.
Admissions to all PG Diploma courses of C-DAC are done
through C-DAC's Computerised Common Admission Test (C-CAT). Candidates have
to apply for C-CAT online at www.cdac.in or acts.cdac.in . Every year,
C-CAT is usually conducted in July(for Sept admissions) and January (for March
admissions).
Candidates will be provided ranks based on their
performance in Section A, Sections A+B, Sections A+B+C of C-CAT. Along
with the ranks, information on how many candidates are there above him/her in the
courses applied will also be indicated.
If a candidate appears for multiple sections, he/she will be provided multiple ranks depending on his/her choice of courses at the time of filling the application form. For example, if a candidate appears for Sections A and B and had chosen courses under Category I and Category II in the application form, he/she shall be provided two ranks: (i) based on the performance in Section A, and (ii) based on the performance in Sections A+B. However, if a candidate appears for Sections A and B but had chosen only courses under Category II in the application form, he/she will be provided only one rank based on the performance in Sections A+B.
Candidates with the lowest 10% performances in Section A, Section B and Section C will not be considered for ranking in any category. Even after the removal of the lowest 10% performers as stated above, if there exist candidates in any category with zero or less than zero marks, then these candidates are also not considered for ranking. The remaining candidates will be ranked based on their performance in Section A (for candidates who have applied for Category I courses), total performance in Sections A+B (for candidates who have applied for Category II courses), and total performance in Sections A+B+C (for candidates who have applied for Category III courses).
Sr No.
|
Event
|
Dates
|
|
1 | Beginning of Online Registration and Application for C-CAT | 28 May 2024 | |
2 | Closing of Online Registration & Application, and Payment of Application Fee | 26 June 2024 | |
3 | Downloading of C-CAT Admit Cards | 2 - 6 July, 2024 | |
4 | C-DAC's Common Admission Test (C-CAT) | 06 July 2024 07 July 2024 | |
5 | Announcement of C-CAT Ranks | 19 July 2024 | |
6 | Online Selection of Courses and Centers (1st Counseling) | 19 - 29 July 2024 | |
7 | Declaration of First Round of Seat Allocation | 31 July 2024 | |
8 | Last Date of Payment of first installment for candidates allocated seats through the first round | 7 August 2024 (till 5pm) | |
9 | Declaration of Second Round of Seat Allocation | 9 August 2024 | |
10 | Last Date of Payment of first installment for candidates allocated seats through the second round | 14 August 2024 (till 5pm) | |
11 | Payment of Caution Deposit and Online selection of course and centre (2nd Counseling) | 16 - 22 August, 2024 (till 5 pm) | |
12 | Declaration of Third Round of Seat Allocation(based on 2nd Counseling) | 23 August 2024 | |
13 | Last Date of Payment of Balance Course Fee | 26 August 2024 | |
14 | Last Date of Registration of Students | 28 August 2024 | |
15 | Start of PG Diploma Courses across India | 29 August 2024 |
The Post Graduate Diploma in Big Data Analytics (PG-DBDA) course will be delivered in fully ONLINE or fully PHYSICAL mode. The total course fee and payment details for the fully PHYSICAL or fully ONLINE mode of delivery is as detailed herein below:
1. PHYSICAL Mode of Delivery:
The course fee for the fully PHYSICAL mode of delivery is INR. 1,15,000/- plus Goods
and Service Tax (GST) as applicable by Government of India (GOI).
The course fee for PG-DBDA has to be paid in two installments as per the schedule.
2. ONLINE Mode of Delivery:
The course fee of the fully ONLINE mode of delivery is INR. 97,750/- plus Goods and
Service Tax (GST) as applicable by GOI.
The course fee for PG-DBDA has to be paid in two installments as per the schedule.
The first installment course fee of Rs 10,000/- + GST on it as applicable at the time of payment is to be paid online as per the schedule. It can be paid using credit/debit cards through the payment gateway. The first installment of the course fees is to be paid after seat is allocated during counseling rounds.
The second installment of the course fees is to be paid before the course commencement through NEFT.
NOTE: Candidates may take note that no Demand Draft (DD) or cheque or cash will be accepted at any C-DAC training centre towards payment of any installment of course fees
1) From the current academic year admissions to all PG
diploma courses will be made through a common Admission test (C-CAT).
2) C-CAT will be conducted in the form of three test papers labeled as
SECTION - A (English, Quantitative Aptitude,
Reasoning, Computer Fundamentals & Concepts of Programming)
SECTION - B (Computer Fundamentals, C
Programming, Data Structures, Data Communications & Networks, Object Oriented
Programming, Operating Systems) (C Programming, Data Structures, Object Oriented
Programming Concepts using C++, Operating Systems & Networking, Basics of Big Data &
Artificial Intelligence)
SECTION - C (Computer Architecture, Digital
Electronics, Microprocessors)
Depending upon the choice(s) of the programme(s) made by the candidate he/she will
have to either appear in just one test paper (SECTION - A) or two test papers
(SECTION - A and SECTION - B) or all the three test papers (SECTION - A, SECTION - B
and SECTION - C).
Depending on the course chosen, candidate need to appear for the test papers
(relevant sections) as per the table given below:
Programme(s) | Test paper(s) to be taken |
PG Diploma in Big Data Analytics (PG-DBDA) |
Section A + Section B |
3) Those Candidates who qualify in C-CAT 2024 (every occurrence) will be offered
admission to various PG diploma courses covered on the basis of their ranks and
choices. There is no age restriction to appear in C-CAT 2024.
4) Candidates may chose one of the dates as per their convenience while filling the
application. The choice of date once made will not be altered unless approved in
writing by C-DAC.
5)C-CAT 2024 will be held on 06 July 2024 and 07 July 2024 Candidates may choose one
of the city as per their convenience while filling the application. The choice of
date once made will not be altered unless approved in writing by C-DAC.
6)To apply for admission to a desired programme, a candidate is required to qualify
in the corresponding test paper(s) and also satisfy the minimum eligibility criteria
of the respective academic programme.
7) There is no age restriction for admission to C-DAC’s PG Diploma courses.
Candidates who have appeared for the final examination of their qualifying degree in
2024 will also be considered for admission to the above courses. By qualifying in
C-DAC's admission tests of July 2024, such university result-awaiting candidates
can apply for provisional admission in August 2024 , subject to the condition
that: (a) All parts of their qualifying degree examination shall be completed by the
date of joining the course, and (b) Proof of having passed the qualifying degree
with at least the required minimum marks shall be submitted at C-DAC by 31 December 2024.
8) The candidates will be provided ranks based on their performance in Section A,
Section A+B, Section A+B+C. If a candidate appears in multiple sections, he/she
shall be provided multiple ranks accordingly. For example if a candidate appears in
Section A and Section B, he/she shall be provided two ranks, based on performance in
Section A and based on performance in Section A and B. A candidate can appear only
in those sections which are chosen at the time of filling in the application. A
candidate, who has not appeared for a particular section, will not get any position
in the merit lists, which span over that section. For each programme a separate
merit list will be prepared from the list of candidates opting for that programme.
Admissions to various programmes at different centres will be made on the basis of
merit in C-CAT 2024 subject to fulfilling of eligibility requirements.
9) Candidates should note that mere appearance in C-CAT 2024 or being in any of the
merit list neither guarantees nor provides any automatic entitlement to admission.
Qualified candidates will have to apply for admission as per the prescribed
procedure. Admissions shall be made in order of merit based on the choice exercised
by the candidate and depending on the number of seats available in the programmes at
the Admitting Centre(s).
10) With regard to the interpretation of the provisions of any matter not covered in
this Information Brochure, the decision of the C-DAC shall be final and binding on
all the parties concerned.
The C-CAT will test the candidate's knowledge of the above topics. The candidate
must possess good knowledge of C Language in terms of the syntax and its appropriate
use. The candidate should carefully study the books recommended herein. However,
merely reading language constructs from the book cannot develop programming ability.
It is absolutely necessary to actually write one's own code in C Language and
implement at least 100 good C Programs on a computer. These programs should be of
increasing complexity and should exploit appropriate constructs and advanced
features of C. Candidates should solve all the problems given in the recommended
books. This will help the candidates in not only mastering the language but also
develop good problem solving ability, which is most critical for any successful
career.
The applicant should also practice the use of good features of the language,
modularize his/her code, put suitable comments to improve readability of the code,
make extensive use of library routines and format the programs to express the
logical flow clearly.
The candidate should note that the rigorous programming practice as prescribed above
is not only required to succeed in the C-CAT but is also required to learn various
modules of PG-DBDA with rapid pace. The rigorous programming practice is in fact the
most important prerequisite to undertake the PG-DBDA Course and possible successful
career in the IT industry thereafter. The candidate may avail the facility of online
Pre-CAT course. The candidate may also contact the nearest Authorised Training
Centre for attending the Pre-CAT course.
The C-CAT will be conducted in computerized mode in
various cities across India.The C-CAT centres will be allocated to candidates on a
first-come, first-served basis of application, depending on the centres' seating
capacity.
The C-CAT date and city once selected in the online application form cannot be
changed unless approved in writing by C-DAC, subject to availability of seats in
requested city. All such signed letters of requests with proof of valid reasons
should be received at C-DAC ACTS, 5th Floor, Innovation Park, Sr. No. 34/B/1,
Panchvati, Pashan, Pune 411008, before the last date of C-CAT application.
CCAT will be conducted in the form of three objective type test papers labeled
as
Section – A (English, Quantitative Aptitude, Reasoning, Computer
Fundamentals & Concepts of Programming)
Section – B (C Programming, Data Structures, Object Oriented
Programming Concepts using C++, Operating Systems & Networking, Basics of Big Data &
Artificial Intelligence)
Section – C (Computer Architecture, Digital Electronics,
Microprocessors)
Every section will have 50 objective-type questions of 3 marks each (maximum 150
marks for any one section). Each objective-type question in C-CAT will have four
choices as possible answers of which only one will be correct. There will be +3
(plus three) marks for each correct answer and -1 (minus one) for each wrong answer.
Multiple answers to a question will be treated as a wrong answer. For each
un-attempted question, 0 (zero) mark will be awarded.
TEST PAPER |
TOPICS |
DURATION |
Section A |
English, Quantitative Aptitude, Reasoning, Computer Fundamentals & Concepts of Programming |
1 hour |
Section B |
C Programming, Data Structures, Object Oriented Programming Concepts using C++, Operating Systems & Networking, Basics of Big Data & Artificial Intelligence |
1 hour |
Section C |
Computer Architecture, Digital Electronics, Microprocessors |
1 hour |
C-CAT. SECTION |
TOPIC |
REFERENCE BOOK |
A |
English |
Any High School Grammar Book (e.g. Wren & Martin) |
Quantitative Aptitude & Reasoning |
Quantitative Aptitude Fully Solved (R. S. Aggrawal) Quantitative Aptitude (M Tyara) Barron’s New GRE |
|
Computer Fundamentals & Concepts of Programming |
Foundations of Computing (Pradeep Sinha & Priti Sinha) |
|
B |
C Programming |
C Programming Language (Kernighan & Ritchie) |
Data Structures |
Data Structures Through C in Depth (S. K. Srivastava) |
|
Operating Systems & Networking |
Operating System Principles (Silberschatz, Galvin,
Gagne) |
|
OOP Concepts using C++ |
Test Your C ++ Skills (Yashavant Kanetkar) |
|
Basics of Big Data & AI |
Fundamentals of Data Engineering (Joe Reis, Matt
Housley) |
|
C |
Computer Architecture |
Computer Organization & Architecture (William Stallings) |
Digital Electronics |
Digital Design (Morris Mano) |
|
Microprocessors |
Microprocessor Architecture, Programming &
Applications with 8085 (Ramesh Gaonkar) |
Schedule of August 2024 C-CAT (The slot
timings may vary slightly. The final timings will be printed on the admit
cards.)
C-CAT Dates |
Test Paper |
Morning Slot Timings |
Afternoon Slot Timings |
6 July 2024 and 7 July 2024 |
Section A |
9:30 am – 10:30 am |
2:00 pm – 3:00 pm |
Section B |
10:45 am – 11:45 am |
3:15 pm – 4:15 pm |
|
Section C |
12:00 noon – 1:00 pm |
4:30 pm – 5:30 pm |
Sr No.
|
Event
|
Dates
|
|
1 | Beginning of Online Registration and Application for C-CAT | 28 May 2024 | |
2 | Closing of Online Registration & Application, and Payment of Application Fee | 26 June 2024 | |
3 | Downloading of C-CAT Admit Cards | 2 - 6 July, 2024 | |
4 | C-DAC's Common Admission Test (C-CAT) | 06 July 2024 07 July 2024 | |
5 | Announcement of C-CAT Ranks | 19 July 2024 | |
6 | Online Selection of Courses and Centers (1st Counseling) | 19 - 29 July 2024 | |
7 | Declaration of First Round of Seat Allocation | 31 July 2024 | |
8 | Last Date of Payment of first installment for candidates allocated seats through the first round | 7 August 2024 (till 5pm) | |
9 | Declaration of Second Round of Seat Allocation | 9 August 2024 | |
10 | Last Date of Payment of first installment for candidates allocated seats through the second round | 14 August 2024 (till 5pm) | |
11 | Payment of Caution Deposit and Online selection of course and centre (2nd Counseling) | 16 - 22 August, 2024 (till 5 pm) | |
12 | Declaration of Third Round of Seat Allocation(based on 2nd Counseling) | 23 August 2024 | |
13 | Last Date of Payment of Balance Course Fee | 26 August 2024 | |
14 | Last Date of Registration of Students | 28 August 2024 | |
15 | Start of PG Diploma Courses across India | 29 August 2024 |
Given below is the computing setup that exists at our
institute. A minimum of 06 hrs per day computer time on a dedicated client node is
to be shared by 2 students. The institute is open 24 hours even on all Sundays /
Holidays.
The evaluation process forms an important part of the
course that leads to conferring the Diploma in Advanced Computing upon the eligible
students.
The evaluation is a continous process that goes on throughout the duration of the
course. Normally, evaluation for each module is carried out as soon as the module
ends and the results for each module are announced within fifteen days of the end of
the module. The final result of the Diploma in Advanced Computing course is usually
declared within 15 days of completing evaluation of the final module of the
course.
The evaluation will consist of three components: a written test, a laboratory test
and ongoing evaluation of lab assignments.
The weightage for each component will normally be:
Weightage | Percentage |
---|---|
Theory examination – (CEE) Conducted By C-DAC ACTS | 40% |
Laboratory examination | 40% |
Internal marks (Lab assignments, surprise tests, viva, seminars etc. ) | 20% |
Operating System Concepts, Software Engineering and Data Communication and Networking. A student will have to score a minimum of 40% marks in each component of the evaluation in order to successfully complete any module. A student will have to successfully complete all modules of the course to be eligible for receiving the Diploma in Advanced Computing. The question papers for the theory as well as the laboratory examinations at all the centers will be set by ACTS, Pune. The evaluation of the written and laboratory will be conducted locally by the centers according to guidelines and model answers provided by ACTS, Pune. The lab examination problems will also be provided by ACTS, Pune.
Grade | Percentage |
---|---|
A+ | 85% and above |
A | 70-84.9 % |
B | 60-69.9 % |
C | 50-59.9 % |
D | 40-49.9 % |
F | Below 40% |
A student who is absent for a test or is unable to successfully clear any module at
the first attempt may be allowed to appear for a re-examination at the discretion of
the course coordinator. However, his score at the re-examination will be de-rated by
20%. Only one re-examination will be conducted.
A student has to successfully complete all the modules and clear both lab and theory
exam in order to be eligible to receive the Diploma in Advanced Computing. Students
unable to complete all the modules within the course duration will be awarded a
certificate for the modules successfully cleared by him/her. No student will be
allowed to appear for any module after completion of the course duration.
Performance statements and certificates will be issued to all students by ACTS, Pune
within 15 days of completing evaluation of the final module of the course.
Installation (Ubuntu and CentOS), Basics of Linux, Configuring Linux, Shells, Commands, and Navigation, Common Text Editors, Administering Linux, Introduction to Users and Groups, Linux shell scripting, shell computing, Introduction to enterprise computing, Remote access.
Cloud Computing Basics, Understanding Cloud Vendors (AWS/Azure/GCP), Definition, Characteristics, Components, Cloud provider, SAAS, PAAS, IAAS and other Organizational scenarios of clouds, Administering & Monitoring cloud services, benefits and limitations, Deploy application over cloud. Comparison among SAAS, PAAS, IAAS, Cloud Products and Solutions, Cloud Pricing, Compute Products and Services, Elastic Cloud Compute, Dashboard.
Python basics, If, If- else, Nested if-else, Looping, For, While, Nested loops, Control Structure, Break, Continue, Pass, Strings and Tuples, Accessing Strings, Basic Operations, String slices, Working with Lists, Accessing list, Operations, Function and Methods, Files, Modules, Dictionaries, Functions and Functional Programming, Declaring and calling Functions, Declare, assign and retrieve values from Lists, Introducing Tuples, Accessing tuples, Visualizing using Matplotlib, Seaborn, OOPs concept, Class and object, Attributes, Inheritance, Overloading, Overriding, Data hiding, Operations Exception, Exception Handling, except clause, Try-finally clause, User Defined Exceptions, Data wrangling, Data cleaning.
Reading and Getting Data into R, Exporting Data from R, Data Objects-Data Types & Data Structure. Viewing Named Objects, Structure of Data Items, Manipulating and Processing Data in R (Creating, Accessing, Sorting data frames, Extracting, Combining, Merging, reshaping data frames), Control Structures, Functions in R (numeric, character, statistical), working with objects, Viewing Objects within Objects, Constructing Data Objects, Packages – Tidyverse, Dplyr, Tidyr etc., Queuing Theory, Non parametric Tests- ANOVA, chi-Square, t-Test, U-Test, Interactive reporting with R markdown, Introduction to Rshiny.
Oops Concepts, Data Types, Operators and Language, Constructs, Inner Classes and Inheritance, Interface and Package, Exceptions, Collections, Threads, Java.lang, Java.util, Java Virtual Machine, Reflection in JVM, JVM’s architecture, Lambda Expressions, Functional Programming and Interfaces, Introduction to Streams, Introduction of JDBC API.
Introduction to Business Analytics using some case studies, Summary Statistics, Making Right Business Decisions based on data, Statistical Concepts, Descriptive Statistics and its measures, Probability theory, Probability Distributions (Continuous and discrete- Normal, Binomial and Poisson distribution) and Data, Sampling and Estimation, Statistical Interfaces, Predictive modeling and analysis, Bayes’ Theorem, Central Limit theorem, Data Exploration & preparation, Concepts of Correlation, Covariance, Outliers, Regression Analysis, Forecasting Techniques, Simulation and Risk Analysis, Optimization, Linear, Nonlinear, Integer, Overview of Factor Analysis, Directional Data Analytics, Functional Data Analysis , Predictive Modelling (From Correlation To Supervised Segmentation): Identifying Informative Attributes, Segmenting Data By Progressive Attributive, Models, Induction And Prediction, Supervised Segmentation, Visualizing Segmentations, Trees As Set Of Rules, Probability Estimation; Overfitting And Its Avoidance: Generalization, Holdout Evaluation Vs Cross Validation; Decision Analytics: Evaluating Classifiers, Analytical Framework, Evaluation, Baseline, Performance And Implications For Investments In Data; Evidence And Probabilities, Explicit Evidence Combination With Bayes Rule, Probabilistic Reasoning, Business Strategy, Achieving Competitive Advantages, Sustaining Competitive Advantages.
Pandas, Numpy, Scipy, Scrapy,Plotly, Beautiful soup
Database Concepts (File System and DBMS), OLAP vs OLTP, Database Storage Structures (Tablespace, Control files, Data files), Structured and Unstructured data, SQL Commands (DDL, DML & DCL), Stored functions and procedures in SQL, Conditional Constructs in SQL, data collection, Designing Database schema, Normal Forms and ER Diagram, Relational Database modelling, Stored Procedures, Triggers. The tools and how data can be gathered in a systematic fashion, Data ware Housing concept, No-SQL, Data Models - XML, working with MongoDB, Cassandra- overview, architecture, comparison with MongoDB, working with Cassendra, Connecting DB’s with Python, Introduction to Data Driven Decisions, Enterprise Data Management, data preparation and cleaning techniques.
Beyond the Hype, Big Data Skills and Sources of Big Data, Big Data Adoption, Research and Changing Nature of Data Repositories, Data Sharing and Reuse Practices and Their Implications for Repository Data Curation.
Introduction of Big data programming-Hadoop, The ecosystem and stack, The Hadoop Distributed File System (HDFS), Components of Hadoop, Design of HDFS, Java interfaces to HDFS, Architecture overview, Development Environment, Hadoop distribution and basic commands, Eclipse development, The HDFS command line and web interfaces, The HDFS Java API (lab), Analyzing the Data with Hadoop, Scaling Out, Hadoop event stream processing, complex event processing, MapReduce Introduction, Developing a Map Reduce Application, How Map Reduce Works, The MapReduce Anatomy of a Map Reduce Job run, Failures, Job Scheduling, Shuffle and Sort, Task execution, Map Reduce Types and Formats, Map Reduce Features, Real-World MapReduce.
Setting up a Hadoop Cluster, Cluster specification, Cluster Setup and Installation, Hadoop Configuration, Security in Hadoop, Administering Hadoop, HDFS – Monitoring & Maintenance, Hadoop benchmarks.
Introduction to Data warehousing and Data lakes, Designing Data warehousing for an ETL Data Pipeline, Designing Data Lakes for ETL Data Pipeline, ETL vs ELT.
Programming with Hive: Data warehouse system for Hadoop, Optimizing with Combiners and Practitioners (lab), Bucketing, more common algorithms: sorting, indexing and searching (lab), Relational manipulation: map-side and reduce-side joins (lab), evolution, purpose and use, Case Studies on Ingestion and warehousing.
Overview, comparison and architecture, java client API, CRUD operations and security
APIs for large-scale data processing: Overview, Linking with Spark, Initializing Spark, Resilient Distributed Datasets (RDDs), External Datasets, RDD Operations, Passing Functions to Spark, Job optimization, Working with Key-Value Pairs, Shuffle operations, RDD Persistence, Removing Data, Shared Variables, EDA using PySpark, Deploying to a Cluster Spark Streaming, Spark MLlib and ML APIs, Spark Data Frames/Spark SQL, Integration of Spark and Kafka, Setting up Kafka Producer and Consumer, Kafka Connect API, Mapreduce, Connecting DB’s with Spark.
Business Intelligence- requirements, content and managements, information Visualization, Data analytics Life Cycle, Analytic Processes and Tools, Analysis vs. Reporting, MS Excel: Functions, Formula, charts, Pivots and Lookups, Data Analysis Tool pack: Descriptive Summaries, Correlation, Regression, Introduction to Power BI, Modern Data Analytic Tools, Visualization Techniques.
Supervised and Unsupervised Learning , Uses of Machine learning , Clustering, K means, Hierarchical Clustering, Decision Trees, Classification problems, Bayesian analysis and Naïve Bayes classifier, Random forest, Gradient boosting Machines, Association rules learning, PCA, Apriori, Support vector Machines, Linear and Non liner classification, ARIMA, XG Boost, CAT Boost, Neural Networks and its application, Tensorflow 2.x framework, Deep learning algorithms, KNN, NLP, Bert in NLP,NLP transformers, NLTK, Introduction to Pytorch framework, AI and its application.
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