AI Career Transition Program

Become an AI Engineer by mastering our syllabus which starts from choosing right AI Solution to building it end-to-end ecosystem and deploying it into embedded devices, mobile, web etc.

Co-Developed by Senior AI Engineers from INTEL

4000+

Learners

9Lac - 56Lac

Avg. Salary/annum

Online

Mode of Learning

6Months

Learning Duration

Industry Specific Projects

15+ Real Life Projects while learning

Live projects going to be provided based on your current experience & industry. 

Get eligibility to collect internship certificate for 6Months

Connect with Trainer's 24x7 help

Build one POC(Proof of Concept) from specific industry with complete solution with deployment

We believe in connecting our trainers with students via whatsapp, linkedin and instagram.

3+ Live Projects Demonstration

Starting from Business Case, Project Charter, Agile, AI Architecture, Software Engineering to final Project release.

No Cost EMI

No need to worry about payment, we got you No cost EMI option. Start now!

MOVE 

AS AN 

AI 

ENGINEER 

3 Hackathon's on AI

Tools Covered

Data Scientist must be flexible with tools and coding. 

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Lead Instructor

Mr. Kanth

Data Scientist | Consultant | Podcaster | Youtuber | Mentor 

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Mr. Kanth is a Data Scientist and Six Sigma Certified. He is a Data Science Consultant for various Top-MNC's like Nokia, EY, Cognizant, BMW etc. He delivered end-to-end AI Solutions using Machine Learning and Deep Learning on Embedded Devices. Built various AI Solutions which impacted financial gains and human effort reduction. 

 

Mr. Kanth is an Orator & Mentor delivered AI, Machine Learning, Deep Learning, IOT, Industry 4.0 & Digital Twin Customised Training Programs across Dubai, Malaysia, Singapore, South Africa, Sudan etc. He delivered more than 100+ trainings on both sides like client side and vendor side. 

Q & A Session from Recently Placed Participants:

We're trying all the possible ways to make your career transition more simplified with Q & A Session from recently placed participants, to build great exposure towards real-time interviews and how every learner need to prepare for their program as well as for their interviews. We host Q & A Sessions from different learners who got placed recently. 

Q & A Sessions helping every learner to crack their Data Science Interviews or AI Interviews with a more simplified approach. 

Program Syllabus

Best in industry career transition based syllabus built by Senior AI Engineers from Intel, NVIDIA, BOSCH etc which helps learners to build knowledge from zero level to real time working confidence on AI Projects.

Program Syllabus

Introduction To AI Course


  • What is AI & Various Branches of AI?
  • Which programming tools are used for AI? Various modes of releasing AI models and their Real time applications
  • Evolution of Artificial intelligence from Rule Based to Artificial Neural Network Based
  • AI Teaching methodologies like Reinforcement Learning, Supervised, Unsupervised & Semi-Supervised Learning
  • Various Artificial Intelligence Algorithms basic intro based on Teaching methodologies
  • Lifecycle of AI Automation & Architecture(ML, DL, Q-Learning etc)




Python


  • Introduction to Python ,IDE, Sypder and Jupyter
  • Installation - Link
  • Different Libraries and their usage




Introduction to List, Tuple, Set, Dict, Scalar, Vector, Matrix, Array, Tensor, DataFrame, Series


  • List and Tuple
  • A Assignment on List, Tuple, Set
  • Set Recap and Dict
  • For loop, While, If, if else, Case, Switch, Escape Sequence




Introduction to Pandas


  • A Assignment on Data Cleaning - Big Data Set
  • Entire Pandas Commands
  • A 10 Mins to Pandas to work on dataset
  • Numpy Commands & Linear Algebra
  • A Assignment on Numpy using Image or 3D data




Machine Learning


  • Linear Regression, Logistic Regression SLR, MLR
  • Correlation, Assumptions of Correlation
  • Linear Regression - Based on two points, OLS
  • Gradient Descent
  • Assumptions of Linear Regression
  • Coding on Linear Regression & Learning Assignment
  • Coding Practice and Break Day
  • Deep Math on Logistic Regression & Coding
  • Hypothesis, Confusion Matrix, Classification Report, ROC and AUC
  • Decision Trees, Random Forest Deep Dive
  • Real time project on Decision Tree, Random Forest




Introduction to Tensorflow 2.0


  • Broadcasting in tensorflow
  • Placeholders, Variables, Constants
  • Different API's in Tensorflow
  • Deep Dive in Tensorflow 2.0 & Various components of Tensorflow




Introduction to Matplotlib & Seaborn


  • Deep Dive into Matplotlib & Seaborn
  • Data Understanding using Matplotlib & Seaborn




Introduction to Scikit - Learn


  • Feature Scaling, Feature Selection, Dimensionality Reduction, Imputation, One-Hot encoding
  • Deep Dive into Scikit Learn




Natural Langauge Processing


  • Deep Dive into NLP & Text Mining
  • Tokenization, Lexical Analysis, Semantic Network, DTM, TFIDF, Coreference Matrix etc
  • Word Cloud, Sentiment Analysis




Deep Learning with Tensorflow


  • Neural Networks
a. Introduction to Neural Networks b. Linking Logistic Regression and Neural Network c. Activation Functions d. Multilayer Perceptron e. Matrix View of Neural Network f. Understanding Backpropagation g. Regularization using Dropout, L1 and L2 h. Relu, Leaky Relu and other Activation Layers i. Advanced Loss Functions
  • Convolutional Neural Network Part-I
a. Introduction to CNN b. Understanding 1D and 2D Convolution c. Conv and Pooling Layers in Keras d. Understanding padding and strides e. Softmax and Dropout Layer f. Autoencoders g. Exercise 5.1: 1D Convolution on relevant data set h. Optimizing with batch normalization i. Understanding padding and strides j. Exercise 5.2: Experimenting with different Optimizers on relevant dataset
  • Convolutional Neural Networks – II
a. Training, Fine-tuning and Prediction in case of Pretrained Models b. VGGNet c. GoogleNet d. Residual Networks e. MobileNet Architecture f. Exercise 6.1: Visualizing ResNet-50 g. Exercise 6.2: Using YOLO for real time object detection
  • Creating a Docker image and Cloud Deployment
a. Introduction to AWS b. Exercise 9.1: Configuring AWS instance c. AWS CLI (Command Line Interface) d. Introduction to Docker e. Exercise 9.2: Containerizing a custom Deep Learning Mode
  • Reinforcement Learning
  • Q-Learning
  • Frozen Lake
  • Project on Reinforcement Learning
  • Game Building
  • Search Algorithms
  • Nega Max algorithms
  • Knowledge Representation
  • Real time project on Game Building





ANY PROFESSIONAL FROM ANY INDUSTRY WITH ANY EXPERIENCE CAN ENROLL FOR THIS PROGRAM.

YOU RECEIVE INTERNSHIP CERTIFICATE BY COMPLETING EVERY PROJECT PROVIDED.

SYLLABUS & TRAINING FORMAT DESIGNED FOR WORKING PROFESSIONALS AS WELL AS FRESHERS.

WE ASSUME OUR LEARNERS ARE FROM BANKING, BFSI, MANUFACTURING, HEALTHCARE, OIL & GAS, RETAIL ETC.

"BEPEC AI Program was lit 🔥, I'm able to answer every interview question with more confidence only because of real time projects. We builded various AI Solutions as projects. But Mr. Kanth demands more time from every learner and he make every student as practitioner."  

Avg. 10+ Career Transitions Every

Month

Every month we are making our students and participants from different backgrounds and different learning formats we're making them to get placed. We fix every block and hurdle to make your career transition simplified.

FRESHERS

Majority of freshers are confused with what to do? How to attend interviews and how to crack them? We support them end-to-end until they get placed.

EXPERIENCED

Making a career transformation with experience is difficult. But we make it possible based on your current experience as reference.

NON-PROGRAMMERS

Non-technical or non-programmers feels pretty confusing to move into data science career. But we take care of your non-programmer journey to Data Scientist.

Best in industry projects to work & to place in resume

Dedicated team to Build your resume

Mock interviews before attending live interviews

Feedback on interviews & support until getting placed as AI Engineer

AI Career Transition Program

Program Main Topics:

Data Science with Python

Advanced Machine Learning & NLP

Live Project Simulation Environment

Interview Preparation Program

CMLA Program

Mock & Resume Building

Deep Learning Advanced with Live Project

Forecasting 

MYSQL 

AI Career Transition Program

Program Main Topics:

Data Science with Python

Advanced Machine Learning & NLP

Live Project Simulation Environment

Interview Preparation Program

Mock & Resume Building

Deep Learning Advanced with Live Project

CMLA Program

Register your seat!!
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