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Data Science with Python Certification Training Course With Placement Assurance

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About Data Science Training Course

Data science is trending as a highly sought-after career among tech enthusiasts and people who want to put in their effort in order to make the tech industry all the more advanced but with that stated, securing a job as a data scientist is easier said than done.

Why?
Well, without proper data science training from an industry recognized technical training academy like Apponix, one can find that they are struggling to keep up with the competition that will be trained in data science courses online. IT companies these days have finally understood that they need professionals who are experts in deriving valuable business-critical information from the data they collect from a plethora of sources. If an IT company wants to invest in data-driven technologies such as automation, machine learning and artificial intelligence then it will need professionals who are highly skilled and have all the prerequisites of a qualified data scientist.

Since, all services that are currently available to people around the world whether it be their streaming service provider to their preferred Search Engine, uses the data driven technologies mentioned above, it is evident that the demand for data scientists will witness an exponential increase in the coming years!

With that stated, if you are on the hunt for quality assured data science training online then choose Apponix – as we have been offering our data science course with placement since 2014.

Over the years, our data science training course has helped countless students find their way amidst the cutthroat competition and secure a high paying job as a data scientist in leading tech companies in India and abroad.

Our data science certificate cost is affordable and at the same time, the data science certificate course lectures are delivered by industry experts who are working professionals in the sector. This allows you to have hands-on experience about what is currently going on in the sector and at the same time, learn neat tricks from the industry expert to find your way around complex problems that you may or may not find yourself in during your time here at Apponix.
For more details, feel free to get in touch with us.

Contact Us

ClassroomOnline You can send course-related emails to my email id.

Data Science Course Objectives

  • Python full coding from scratch
  • Visualization with Python
  • Statistics - theory and application in business
  • Machine Learning with Python - 6 different algorithms
  • Multiple Linear regression
  • Logistic regression
  • Variable Reduction Technique - Information Value
  • Forecasting - ARIMA
  • Cluster Analysis
  • Decision Tree
  • Random Forest
  • Case studies on Machine Learning (18 case studies)
  • SQL queries(with Python)
  • Business Presentation of Technical Solution in-front of end client.
  • Robotic Automation(with Python)
  • CV Building activities
  • Interview preparation
  • Mock Interview sessions

Our Recent Batches

Data Science Course Syllabus

Machine Learning with Python

  • 1:Introduction to Python Programming Language

  • Introduction and Installation of Python software Python packages: Pandas, & Numpy
  • Concepts of Data frame Filtering
  • Loc and iloc for filtering Usage of Boolean in Filtering Appending

  • 2: Data handling in Python

  • Handling of Missing values If else statement
  • Extra trick of using if else statement Removal of Duplicates
  • Frequency Distribution
  • Merging – Inner, Outer, Left and Right Binding and Appending
  • Descriptive Statistics
  • Inbuilt Numeric functions of R

  • 3: More data handling using Python

  • Pivot Table of Excel in Python Grouping function
  • Learning of SQL queries using Python Grouping numeric data

  • 4: Additional functions of Python

  • Text functions
  • Data cleaning with efficient text functions Inbuilt String functions of Python Reshape functions of Python

  • 5: Statistic

  • Everything you want to know about statistics….Well sort of!! Mean, Median, Mode
  • Standard Deviation, Variance, Normal Distribution Hypothesis testing
  • T-test, Anova, Normality test

  • 6: Linear Regression

  • Predictive Analytics – Linear Regression Concepts of Linear Regression
  • Simple and Multiple Linear Regression Automatic Dummy Variables creation technique Model Validation parameters
  • Model Assumption testing
  • Splitting of data for Validation and testing
  • Business Case Study with real data to model in Python

  • 7: Linear Regression Practice Case Study

  • Participants will be asked to develop a Linear Regression model on a real life data, in presence of the instructor. Time given is 2.5 hours. Participants will be treated like an industry employee, but in terms of help certainly the instructor will not be as ruthless as the boss. After completion of the model (with the help of the instructor wherever it is required), the instructor will show how to present a model to a real life client.

  • 8: Logistic Regression

  • Predictive Analytics – Logistic Regression Concepts of Logistic Regression
  • Difference between Linear Regression and Logistic Regression Automatic Dummy Variables creation technique
  • Model Validation parameters Model Assumption testing
  • Splitting of data for Validation and testing
  • Business Case Study with real data to model in Python

  • 9: Logistic Regression Practice Case Study

  • Participants will be asked to develop a Logistic Regression model on a real life data, in presence of the instructor. Time given is 2.5 hours. Participants will be treated like an industry employee, but in terms of help certainly the instructor will not be as ruthless as the boss. After completion of the model (with the help of the instructor wherever it is required), the instructor will show how to present a model to a real life client.

  • 10:Time Series Forecasting

  • Time series forecasting: ARIMA
  • Difference between forecasting and prediction Concepts of time series data
  • Concepts of ARIMA
  • Descriptive analytics for ARIMA Development of model
  • Best model selection Forecasting with the best model Residual analysis
  • Business Case Study with real data to model in R software
  • Participants will be asked to develop a model in presence of the instructor.

  • 11: Cluster Analysis

  • Unsupervised Machine Learning with R Cluster Analysis: Concepts
  • Cluster analysis with R – K Means, Hierarchical etc.

  • 12: Decision Tree and Random Forest

  • Concepts of Decision Tree Decision Tree with Python Concepts of Random Forest Random Forest with Python

R Programming

  • 1: Introduction to R Programming Language

  • Introduction and Installation of R software R packages
  • Concepts of Vector – Numeric, Character, and Factor Concepts of Data frame
  • Filtering
  • Usage of Boolean in Filtering Sorting
  • Reshape of data using Tidyr package

  • 3: More data handling using R

  • Pivot Table of Excel in R Table function
  • Count function of plyr package Learning of SQL queries using R Grouping numeric data
  • User defined functions (Macros) in R Visualizing of Data

  • 2: Data handling in R

  • Handling of Missing values If else statement
  • Extra trick of using if else statement Removal of Duplicates
  • Merging – Inner, Outer, Left and Right Binding and Appending
  • Text functions
  • Data cleaning with efficient text functions Inbuilt Numeric functions of R
  • Inbuilt String functions of R Inbuilt other functions of

  • 4: Additional functions of R

  • Date functions with Lubridate package Apply functions
  • User defined functions (Macros) in R Visualizing of Data

Data Analytics with MS-excel

  • 1: Introduction to Excel

  • Introduction to Excel Workbook and worksheets Entering data into the spread sheet Undo & Redo Adding Comments
  • Formatting and conditional formatting All types of borders Moving & Coping and inserting data Finding and replacing Filtering and Sorting of data
  • Logical operators Practice sessions

  • 3: Analytics with Excel

  • Pivot Table
  • Data manipulation with pivot tables Pivot table charts Data visualization with Excel
  • Practice sessions

  • 2: Different Functionalities of MS Excel

  • Text to column V-look up Duplicate removal Concatenate
  • Functions of excel – Logical, Mathematical, Statistical, Others Practice sessions

  • 4: Advanced Analytics with Excel

  • Pivot Table
  • Functions of excel – Financial functions What if analysis – Goal Seek, Solver etc. Macros
  • Analytics using Excel Practice sessions

Benefits of learning Data Science Training

Data science related courses from Apponix will let you make the most out of the demand for skilled professionals in this sector so that you can land a high-paying job at a respectable firm or an MNC for that matter in no time! With our data science certificate online or offline course, you will surely be able to have a competitive edge over other applicants interested to have a lucrative career in the field of data science.

Related job roles

  • Data Analyst
  • Data Scientist
  • Analytics Manager/Lead
  • Machine Learning Engineer
  • Statistical Programming Specialist

Skills covered

  • Introduction to Python Programming Language
  • Statistics
  • Linear Regression
  • Logistic Regression
  • Time Series Forecasting
  • Cluster Analysis
  • Decision Tree and Random Forest
  • Machine Learning with R
  • Data handling in R
  • Microsoft Excel and Advanced Functionalities

Course features

  • Guaranteed Placement
  • Guaranteed 5 Interview Calls
  • Lectures Will Be Delivered By Senior Data Scientist From And MNC
  • Dedicated HR Team For Placement Support
  • Access To Student Web Portal

Training Options

Online and offline classes are available
Details are as follows –

Online classes
  • Only 8 to 10 students in a batch
  • Learn from industry experts
  • Personal attention will be given to each student
  • Flexible class timings
  • Regular assessments and assignments are provided to maximize learning.
In-classroom session
  • Intensive classroom training
  • Only 8 to 10 students in a batch
  • Practical-based training program
  • Internship support
  • Regular assessments and assignments are offered.

Eligibility /prerequisites

Before you enroll for Python for Data Science Courses, you need to have basic knowledge of statistics and previous encounters with prominent programming languages such as Python. Secondly, you need to have an analytical mind – that is all you would need to enroll for Statistics For Data Science Courses.

Exam & certification on Data Science Training

Our complete data science bootcamp does not come with exams and certification but an industry-recognized data science course completion certificate will be offered after you score 80 % at the one-hour-long exam we will conduct that will contain 25 objective type questions about the course.

Students Feedback for Data Science

reshma
Resham Rajpal

The training at Apponix made me more confident in Data analysis. I have completed Data Science training form here. Excellent classes that helped a lot.

Data Science Expert
chauhan
Suryadeep C

My experience with Apponix was really great. The trainer provided a lot of practical training. He is an expert. Each topic was taught through proper practical classes.

Data Science Analyst
mahesh
Mahesh Mahi

I took Data Science training from the institute. I’m happy to make Apponix as my choice. Too good labs and sessions are handled here.

Data Science Analyst
Shubhojit Mr Shubhojit- Senior Data Scientist

Data Science Trainer 12+ Years Of Working Experience in MNC.

Data Science Trainer Profile

  • He is a senior data scientist currently working at an MNC
  • He also has been training aspiring data scientists at Apponix for the last 12 + years.
  • He has trained more than two thousand students over the years
  • He is a master of delivering lectures on data science in the most lucid words so that everyone in his class can understand even the intricate parts of the curriculum.
  • He always demonstrates his abilities as a student focused trainer who has a knack for clearing all the doubts of his pupils but never shying away from the core discussion.
  • He is known for his enthusiasm related to data science and his ability to take unique training techniques in a bid to make his training sessions interesting for students.

Apponix Ratings

1000+ Satisfied Learners

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Student Review

Lakshana Senthil quotes
Lakshana Senthil
Data Engineer

Management is very good, flexible with timings. Teaching pattern is easy and understandable.

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Ajith Bahadhur
Data Analyst

I took training for Data Science from Apponix institute, tutor has good knowledge on the subject & very experienced, he makes understand every concept and he will clear the doubts again & again, i gained more knowledge on Data Science.

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Bijal Patel
Data Analyst

Best institute for Data Science. Trainer has very good knowledge in Data Science.

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Vamshi Krishna quotes
Vamshi Krishna
Data Engineer

Sir is very helpful and takes every step to make the students understand topics.

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Taniya Nabi quotes
Taniya Nabi
Data Analyst

It is good to learn Data Science here and the tranier is excellent.

Read More

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Salary expectation after completing Data Science course

As there is a growing demand for Data Science Engineers, the salary is also constantly increasing for Data Science skills,
As per payscale.com Average salary for Data Scientist is Rs 9,12,453 Per year.

Career after Data Science course

Large number of IT companies spread across World, you should not have any doubt on shortage of Data Science jobs. IT technologies is growing and there a huge demand for Data Science engineers. Data Science has more than 70% of the markets share in terms of providing services.

Data Science classroom training

Apponix technologies now offers a data science course, the best data science course in the market, covering the complete Data science concepts from basic to expert. We offer services from training to placements as a part of this data science course. Get answers to all the queries till your course completes.

Data science course in Electronics city

Apponix has been offering data science courses since 2014 and has helped a lot of students in getting their dream job. If you want to learn everything about data science from basic to advanced with the industry level experienced trainers, then you should learn from us and get prepared for the future.

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Data Science Job Responsibilities

  • Modify existing databases and database management systems (DBMS) or instruct programmers and other analysts to make essential changes.
  • Write and code logical and physical database descriptions and specify identifiers of database to management system or direct other colleagues in coding descriptions.
  • Review project requests describing database user needs to estimate time and cost required to accomplish project.
  • Review data results to ensure accuracy. Configure data visualizations for stakeholders
  • Provide data analysis and standard reporting support, which includes the ability to extract data from various sources and data stores by executing light business coding (SQL, VBA, Unix, etc.) and system parameter setting, perform ad-hoc queries and develop/automate financial/statistical models using a variety of known software applications and tools (Excel, Access, etc.)
  • Support the use of data science and machine learning within the various PSE engineering DevOps teams.
  • Manipulate and analyze complex, high-volume, high-dimensionality data from varying sources using a variety of tools and data analysis techniques
  • Translates business requirements throughout the development process, delivers solutions in accordance with business strategies, standards, and processes.
  • Develop business cases for R&D initiatives, provides expert advice to product managers, developers, architects and business partners on data science use cases and options.
  • Architect highly scalable distributed systems, using different open source tools.
  • Working with lambda architectures and batch and real-time data streams.
  • Understand high performance algorithms and Python statistical software and brief team.

FAQs

What do you mean by data science?

  • Data science is an umbrella term for the processes a data scientist uses to uncover patterns all the while extracting business-critical information from huge amounts of data derived from various sources.

    • What is the objective of data science?

  • Exploring, sorting and analyzing big data obtained from various sources in a bid to optimize the internal and external processes of a business is the primary objective of data science.

    • Why I should be a data scientist?

  • Because it is rated as one of the top job sectors in terms of career growth opportunities, job satisfaction and pay scale. Furthermore, the demand for data scientists is always high as the number of skilled professionals is comparatively less.

    • Who are ideal candidates for this course?

    Professionals like –
  • Professionals like –
  • Banking and Finance Professionals
  • IT Professionals
  • Analytics Managers
  • Business Analysts
  • Marketing Managers
  • Supply Chain Network Managers
  • Graduates with a Bachelors or Master’s degree – are the ideal candidates for this course.

    • Is machine learning a part of the data science training course?

  • Yes, machine learning is a part of data science.

    • What is machine learning?

  • It is a method of analyzing data. It is also a part of artificial intelligence as it allows computer systems to identify patterns and make decisions without any help from humans.

    • Can I learn data science even if I don’t have any prior knowledge about this field?

  • Yes, you can learn data science even if you do not have any prior knowledge about this field as we will also take classes on basic concepts of data science.

    • Is it necessary to know how to code if I want to become a data scientist?

  • Yes, you need to have basic knowledge about various programming languages like Python, C/C++, SQL, and Java alongside a basic understanding of computer coding.

    • Is the course easy to understand?

  • Yes, you need to have basic knowledge about various programming languages like Python, C/C++, SQL, and Java alongside a basic understanding of computer coding.

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