PG Diploma in Data Science and Machine Learning

100% JOB Assured with Globally Accepted certificate

Eligibility: BE, B.Tech, ME, M.Tech

Intermediate

Overview

PG Diploma in Data Science and Machine Learning

Description

The PG Diploma in Data Science and Machine Learning is a five-month professional program that provides in-depth data science knowledge and expertise.

Cranes mentors engineers in all critical disciplines to assist them in excelling at designing Data Science based applications that meet industry standards.

Cranes provide students with a structured framework to help them develop technical skills and knowledge. The lectures are well-planned and delivered with examples to make them more interesting and understandable. We want to help students develop a much broader range of mental representations of knowledge.

Cranes Varsity is considered as the best Data Science Course (Available Online) which offers services from training to placement as part of the Data Science training program with over 400+ participants placed in various multinational companies including Genpact, Ernst & Young, Capgemini, Vodafone, CGI, Wipro, Tata Elxsi, IBM, Lumen Technologies, Tech Mahindra, Birla Soft, HTC, Happiest Minds, Western Digital, Mearsk Global, Koireader, K7 Computing, Mphasis, Atos, Latent View, etc.

We offer the highest quality teaching, assessment and placement support through our Data Science course. The course is designed to make a novice into an expert from developing Python programming, and writing queries on SQL to building Machine learning & Deep Learning Models and Cloud computing. Our Lead mentors are industry experts and have been associated with us for decades.

If you’re looking toward building your career in Data Science and are interested in getting the Data Science Course with Placement, then Cranes Varsity is the right destination for realizing your aspirations and growing on your Career ladder.

Data Science using Python training course syllabus is classified into modules that help students better understand the subject. Which are listed below:

Course Modules

Generic

  • RDBMS using MySQL
  • Python for Data Science
  • Advanced Python (Testing and Web Scraping)
  • Exploratory Data Analysis using Pandas

Data Science Specialization

  • Mathematics and Statistics for Data Science
  • Machine Learning using sklearn
  • Machine Learning model Improvement
  • Deep Learning using Tensor Flow
  • Data Analysis and Visualization using Tableau
  • Natural Language Processing

Projects

  • Apply statistical methods to make decisions in various business problems, including bank, stock markets, etc.
  • Apply regression to predict future flight price
  • Apply classification to classify customer
  • Use clustering to cluster banking customers
  • Computer vision projects like Face recognition, Image Quality Improvement, etc.

Platform

  • Anaconda Distribution Jupyter, Spyder
  • Tableau
  • Google Colab

Course Content

Generic:

  • Introduction to Python
  • Python Functions
  • Scope of Variables
  • List and Tuple
  • Map and filter functions
  • Set and Dictionary
  • Python Data types and Conditions
  • Default arguments
  • Global specifier
  • List Methods
  • String
  • Exception Handling
  • Control Statements
  • Functions with variable number of  args
  • Working with multiple files
  • List Comprehension
  • List comprehension with conditionals
  • File Handling

  • Object Oriented Programming
  • Multiprocessing
  • Argument Passing to thread
  • Regular Expression
  • Testing Fundamentals
  • Overloading Operator
  • Multi-threading
  • Sharing data between threads
  • Finding Patterns of Text
  • Unit Testing
  • Inheritance
  • Creating Thread
  • Race Condition
  • Meta characters
  • Working with JSON

  • NumPy
  • Slicing of Matrices
  • NumPy Functions across axis
  • Pandas Series
  • Pandas Data frame
  • Working with Categorical Data
  • Sorting Data Frames
  • Creating graphs using Matplotlib
  • Scatter Plot, Line Graph
  • Seaborn
  • Vectorization
  • Filtering
  • Stacking of arrays
  • Data Cleaning
  • Selection Data (loc, iloc)
  • Grouping & Aggregation
  • Importing csv files
  • Customizing Plots
  • Bar Graph, Histogram
  • Matplotlib
  • Broadcasting
  • Array Creation Functions
  • Matrix Calculation
  • Handling Missing Data
  • Filtering Data Frames
  • Merging Data Frame(concat, merge)
  • Importing Excel Files
  • Saving Plots
  • Subplots

  • NumPy
  • Slicing of Matrices
  • NumPy Functions across axis
  • Pandas Series
  • Pandas Data frame
  • Working with Categorical Data
  • Sorting Data Frames
  • Creating graphs using Matplotlib
  • Scatter Plot, Line Graph
  • Seaborn
  • Vectorization
  • Filtering
  • Stacking of arrays
  • Data Cleaning
  • Selection Data (loc, iloc)
  • Grouping & Aggregation
  • Importing csv files
  • Customizing Plots
  • Bar Graph, Histogram
  • Matplotlib
  • Broadcasting
  • Array Creation Functions
  • Matrix Calculation
  • Handling Missing Data
  • Filtering Data Frames
  • Merging Data Frame(concat, merge)
  • Importing Excel Files
  • Saving Plots
  • Subplots

Placement Statistics

FAQs

Career opportunities are very high with high pay packages compared to other domains, Roles like Data scientist, Data analyst, business analyst, Data analytics manager, Business intelligence manager and many other roles can be expected.

Having prior knowledge of any programming language is an added advantage but not mandatory, and the basics of linear algebra are a must.

Having a good knowledge of Python Programming concepts, and a good hold on linear algebra. 

Yes, you can learn Machine Learning Course completely online.

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Duration: 5 months
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