Social Prachar

"Hyderabad's 1st Company owned Training Center for Data Science & AI"

#RewardYourSelf A Recession-Proof AI Career in 2024

Become an IBM Certified Data Scientist in just 150 Days
New Batch Starts on 15th MAY with just 10-15 students

🔥 Only ONE Batch per Month

🔥 Just 20 Students Per Batch

🔥 Course & Internship Program

🔥Online & Classroom Programs

Artificial Intelligence Mastery Course Includes Python, Statistics, Machine Learning, SQL, Tableau, Deep Learning, Tensorflow, NLP, Computer Vision

  1. Offline/Online Batches Available
  2. Receive Globally Accepted MNC Certification
  3. Backup Sessions & Recorded Videos for Future Reference
  4. 1-1 Dedicated Career Success Manager
  5. Life-Time Access to Digital Learning Portal(LMS)
  6. 1-1 Resume Screening & Interview Guidance
  7. 100% Paid internships & Full-time Opportunities
  8. Industry Job Ready Curriculum with 20+ Real-Life & Capstone Projects
  9. Free Soft Skills & Interview Skills Sessions
  10. ✅ SocialPrachar is the First Institute in Hyderabad which Introduced Advanced Data Science AI Program in 2015
  11. ✅Socialprachar has Trained over 3000+ Students in Data Science, AI since 2014
  12. ✅Received 7 Prestigious Globally Recognized Awards in Ed-Tech
  13. ✅ Recently India’s Top Rated Magazine “Times of India” Featured Socialprachar as 

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Certificate of Excellence Award

Academy of the Year 2019 - 20

We are happy to announce that Social Prachar has been awarded as the Best Academy of the Year 2019 – 2020 @7th Asian Education Summit, Mumbai Presented by Juhi Chawla, former Miss India

Yay! SocialPrachar Got Featured in

“Master Data Science with AI”

“58 Million Jobs to be Created in Next Few Years”

According to the World Economic Forum Report. The growth of Artificial Intelligence could create 58 million jobs in next few years.

Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think. It  is a field of Computer Science that gives computers the ability to learn without being explicitly programmed.

Artificial intelligence is a science and technology based on disciplines such as Computer Science, Biology, Psychology, Linguistics, Mathematics, and Engineering.

AI Job Roles Available

AI Engineer
AI Specialist
Machine learning engineer
Data scientist
Research scientist
Business intelligence developer
Computer vision engineer


Who to Join AI

Post Graduates
IT Professionals
Data Analysts, Business Analysts
Python Professionals
Also, anyone having interest to learn Artificial Intelligence

Our Expert Trainers from

We are proudly launching 7 month Specialization course on Artificial Intelligence

Talk to us on WhatsApp

  • According to Market estimates, close to 1,20,000 positions related to Analytics & Data Science are currently available to be filled in India.
  • This is almost a 45% jump in the open job requirements, compared to last years’s employment ratio.
  • Compared to worldwide market estimates, India contributes 8% of open job openings currently. Growth in the number of data science jobs globally was very much higher than in India but India will lead the job growth market by 2x before 2022.
  • The top 10 leading organizations with the most number of analytics openings this year are – Accenture, Amazon, KPMG, Honeywell, Wells Fargo, Ernst & Young, Hexaware Technologies, Dell International, eClerx Services & Deloitte.
  • Almost 90% of analytics jobs advertised in India are on a full-time basis. Just 10% form the part-time, internship, or contractual jobs.
  • Top designations advertised are: Data Scientist, Data Engineer, Analytics Manager, Business Analyst, Research Analyst, Data Analyst, SAS Analyst, Analytics Consultant, Statistical Analyst, etc
  •  Top industries hiring analytics talent: BFSI sector has the maximum demand for data science skills in India followed by e-commerce and telecom, Banking, etc 
  • Increase in Data Science jobs offering more than 15 lakh per annum based on the experience of the candidate, companies, and their requirements.
  • The current Hiring trend indicates demand for junior level talent rises According to our estimate, as compared to the previous year Senior profiles are always the Hottest in the market.

Industry Recognitions

AI Course Content

I. How to Be Successful with this Course

  • Train Your Brain
  • Methodology to Understand the Concepts Faster and Not Forget
  • Prepare Your Own PDF Material from IPython Notebooks
  • Plagiarism
  • Saving Your Work
  • Error Debugging


Module 1-Introduction to course

  • Introduction to corporate training
  • Software life cycle
  • Methodologies
  • Soft skills
  • Professional Ethics
  • Make you strength
  • Where I Stands?

    Module 2-Data science AI introduction

  • What is data science
  • Need for data science?
  • Data science vs Business Intelligence
  • Prerequisite for learning data science
  • What does a data scientist do?
  • Data science life cycle with example
  • Demand for data science

    Module 3-Installations

• Installations required for data science

Module 4 -Python programming

  • Introduction to python
  • Operators
  • Data Types
  • Control Statements
  • Functions
  • Data Structures – Lists, Sets, Tuples, Strings, Dictionaries,
  • OOPS Concept


    Module 5 -Libraries

    • Numpy
    • Pandas
    • Scipy
    • Scikit-Learn • Keras

    • Matplotlib • Seaborn
    • Cufflinks • NLTK

    Note: Installations and work end to end. As per requirements going to work with different libraries.

Module 6 – Data Exploration

  • Collecting data from different sources
  • Analyzing data
  • Data preprocessing
  • Data munging
  • Data mining
  • Data manipulation
  • Data visualization
  • Feature Selection
  • Feature Scaling
  • Dimensionality reduction

    Module 7 -Statistics

  • Basics of Statistics
  • Descriptive Statistics
  • Inferential Statistics
  • Qualitative vs. Quantitative Analysis
  • Hypothesis Testing
  • Data Distribution

    Module 8 – Other Mathematics Concepts

  • Probability
  • Calculus
  • Linear algebra

    Module 9 -Machine Learning

  • Introducing Machine Learning models
  • Supervised learning
  • Regression and Classification models
  • Unsupervised learning
  • Clustering and Aggregation models
  • Semi supervised learning
  • Over fitting and under fitting(Linear, Logistic, Navi Bayes, K-Nearest Neighbors, Support Vector Machine, Decision Trees, Random Forest …..)Note: Deals with Mathematics and Programming part

    Module 10 -Deep Learning and other algorithms

  • Introduction to Deep learning
  • OpenCV
  • Artificial Neural Networks
  • Convolutional Neural Networks
  • Recurrent Neural Networks
  • Tensor flow
  • Over fitting and under fitting

Module 11 -Natural Language Processing

  • Introduction to NLP
  • Text Preprocessing
  • Lemmatization
  • Stemming
  • Text to features
  • Important Tasks in NLP
  • Important Libraries for NLP

    Module 12 – Computer Vision


  • Examine your problem
  • Prepare your data (raw data, feature extraction, feature engineering, etc.)
  • Spot-check a set of algorithms
  • Examine your results
  • Double-down on the algorithms that worked bestNote: Deals ‘n’ number of real time projectsWORK ENVIRONMENT
  • Status meetings
  • Meetings with stockholders
  • Participating in gathering requirements
  • Working on client projects
  • Coordinating team

System Requirements

  • Ram 4GB Min
  • Hard Disk 250GB
  • Processor i3 Min

II. Monthly Tests

III. Mock interviews

IV. Certifications


Artificial Intelligence Course Highlights

1.  A Dedicated Portal For Practicing.
2. Real Time Project Data Models to Work
3. 1-1 Mentorship
4. Internship Offers for Freshers.
5. Weekly Assignments.
6. Weekly Doubt Sessions
7. Advanced Curriculum
8. Certificates On successful Completion of Project .
9. Resume Preparation Tips
10. Interview Guidance And Support.
11. Dedicated HR Team for Job Support And Placement Assistance.
12. Experienced Trainers.

Get Instant replies via WhatsApp! Chat

Also Read

Top Artificial Intelligence(AI) Companies in India (City-Wise)

Difference Between Artificial Intelligence-Machine Learning and Deep Learning

2020 – Year of AI | Telangana Government declared 2020 as Year of Artificial Intelligence

How to Build a Career in AI and Machine Learning?

Why Artificial Intelligence Course?

  1. To Create Expert Systems: The systems which exhibit intelligent behavior, learn, demonstrate, explain, and advice its users.
  2. To Implement Human Intelligence in Machines: Creating systems that understand, think, learn, and behave like humans.
  3. The goal of AI is to develop computers that can simulate the ability to think, as well as see, hear, walk, talk, and feel.

Real-Life Applications of AI

  1. Expert Systems

The expert systems are the computer applications developed to solve complex problems in a particular domain, at the level of extra-ordinary human intelligence and expertise.

Examples: Flight-tracking systems, Clinical systems

  1. Natural Language Processing

Natural Language Processing (NLP) refers to AI method of communicating with an intelligent systems using a natural language such as English.

Examples: Google Now feature, speech recognition, Automatic voice output

  1. Neural Networks Examples

Yet another research area in AI, neural networks, is inspired from the natural neural network of human nervous system.

Examples: Pattern recognition systems such as face recognition, character recognition, handwriting recognition.

  1. Robotics

Robotics is a branch of AI, which is composed of Electrical Engineering, Mechanical Engineering, and Computer Science for designing, construction, and application of robots.

Examples: Industrial robots for moving, spraying, painting, precision checking, drilling, cleaning, coating, carving etc.

5. Fuzzy Logic

Fuzzy Logic (FL) is a method of reasoning that resembles human reasoning. The approach of FL imitates the way of decision making in humans that involves all intermediate possibilities between digital values YES and NO.

Examples: Consumer electronics, automobiles, etc

“Combine the power of Data Science, Machine
Learning and Deep Learning to create powerful AI
for Real-World applications”

Call Our Career Advisor Now for
Requisite Details.

Frequently Asked Questions

Predictions suggest that by 2025, AI will generate 97 million new job opportunities. However, numerous businesses are facing challenges in locating proficient individuals capable of developing, training, and managing AI and ML systems. For those contemplating a career transition, we’ve assembled a selection of AI roles expected to experience significant demand in the upcoming years.

A high level of confidence indicates that the salary data is derived from a significant number of recent reports. In India, the salary for AI Engineers typically falls within the range of ₹3.0 Lakhs to ₹22.0 Lakhs annually, with an average of ₹11.6 Lakhs per year. These estimates are drawn from a pool of 720 recent salary reports submitted by AI Engineers.

Indeed, artificial intelligence (AI) presents a highly promising career trajectory in India, brimming with enticing prospects and robust growth avenues. India is currently witnessing a notable upswing in the integration of AI across diverse domains such as healthcare, finance, e-commerce, manufacturing, and agriculture.

In India, the salary packages for Artificial Intelligence professionals vary significantly. Entry-level positions typically offer starting salaries ranging from approximately Rs. 6 LPA to Rs. 12 LPA. However, top-tier companies such as Amazon, Flipkart, Google, Facebook, and others often provide more lucrative compensation packages towards the upper end of this spectrum.

Many firms provide opportunities for artificial intelligence roles in data science due to the substantial demand for professionals in this domain. Consequently, even entry-level candidates receive lucrative monthly salaries in artificial intelligence positions.

Indeed, the abundance of artificial intelligence (AI) jobs is evident, with hiring increasing by 32% over the past few years. However, a significant talent gap persists, as there are insufficient qualified applicants to fill the growing number of vacant AI positions.