IT JOBS FOR FRESHERS AND EXPERIENCED
GTTP – We have come further to provide an amazing opportunity to IT professionals with experience between 0-5 years to start their career in Germany. It is not just the career you get but the additional skills you learn. You are expected to attain training and work at the same time.
By Pursuing IT job course with Gotogermany the employment prospects in Germany is very good.
Stages of GTTP:
IT Fresheres can choose from any of these two programs
AR/VR program · 6 months of training · 0 to 5 years experience · B1 level german training · Minimum 60% in bachelors or masters · Any bachelors with 60% marks in there academics | DATA SCIENCE · 6 months of training · 0 to 5 years experience · B1 level german training · Minimum 60% in bachelors or masters · Only students from computer science related fields |
Certification:
Trainees have to attend an examination to assess what they have learned.
There will be final exams at the end of the training and as a rule,After clearing the final exams, One stands a good chance of starting a successful career in Germany.
Eligibility:
- Bachelors in computer related degree with minimum of 60% in there academics, for data science
- Students with 60% in there academics for AR/VR.
- Basic screening test in python/c++ and should secure 70% for a data science program.
Language qualification:
B1 Level Certification is mandatory
(Gotogermany also provides training in Germany in contract with TELC AND Goethe)
- Shortlisting the resume that matches the requirements.
- Gotogermany Interveiw, where gotogermany asses whether they fit the requirement.
- 6 months course in Data science or AR / VR.
- Students should parallelly learn B1 language, where gotogermany also helps in contract with the TELC AND GOETHE institutes.
- Candidates having B1 level certification, offer letter will be released and 25% of the payment must be done, which is non-refundable.
- If the candidate don’t have B1, they should learn upto german B1 level, make 25% of the payment and then the offer letter will be released.
- Visa application process will begin only after completion of B1 certification, where our company will be assisting through out the process, 50% of signup amount is to be paid.
- Once the visa is approved the last 25% of the signup amount should be paid.
- All set to fly germany, where company helps you with the accomodation and other details.
Visa for Citizens from other countries
EMPLOYMENT VISA
- All necessary documents
- Bachelor degree
- Minimum 0 to 5 years of work of experience in your field of study
- Offer letter from germany companies(which gotogermany provides )
- Show proof that you have enough funds to support yourself in the mean time of job search
- Should have medical or travel insurance during your stay for 6 months of visa permit
Health Insurance:
- From the first day of your stay in Germany health insurance is mandatory
Visa process is completely assisted by gotogermany team to meet the eligibility.
Document Checklist:
- Valid national passport.
- Proof of residence(Driver’s Licence, Utility Bill(Past 6 months from now)).
- Health insurance.
- Curriculum Vitae.
- Proof of Qualification.
- Personal covering letter.
- Police Clearance
- Proof of paid visa fee.
- Declaration of Accuracy of Information.
- Notarized copy of the 10th-grade certificate
- Notarized copy of the 12th-grade certificate
- Notarized copy of other vocational training or further graduation (if any)
- Resume in tabular form with educational background 1st to 12th grade (including photo, percentage of the results of 10th and 12th grade, place, date, signature) as .doc file
- Notarized Passport Copy
- Passport size photo in good resolution
- B1 certificate (needs to be available before the visa interview)
Curriculum
XR Foundation – Level 0
(Theory/Demo) – DURATION 90 HOURS
- Introduction to AR / VR / MR (XR) with demos
- Difference between 2D & 3D
- Workflow on a 3D software(Blender 3D/ Maya 3D)
- Aspects of gaming versus non-gaming
- What is XR? Augumented, Virtual and Mixed Realities analysis
- Intro on Augumented Reality
- Marker and Marker-Less
- How to build a basic AR/VR app
- Vuforia (cloud and device based)
- Unity 3 D
- Importing SDK into Unity 3D
- Setting up AR scene
- Vuforia access keys
- Building APK
- App Demo and Architecture
- Intro into Apple ARkit & Google ARcore Demos
- Real world applications, a glimpse
- Whats next?
XR Intermediate – Level 1
(75 Hours Theory & 225 Hours Practical) – DURATION 300 HOURS
- Unity Interface Overview
- Canvas & UI
- Inspector,Prefabs,Game Objects
- Basic Programming in C#
- Playtest & Runtime in Unity 3D
- Vuforia & Its Developer Portal
- Object Recognition
- Image Targets
- Blender 3D/ Maya 3D/ Photoshop Basic
- Handle Unity 3D/2D assets basic
- Hololens SDk development basic
- App Development Publish
XR Advanced – Level 2
(75 Hours Theory & 225 Hours practical) – DURATION 400 HOURS
- Multi targers
- Smart Terrain
- Virtual Buttons
- Cloud Recognition
- Video playback/Stereo Rendering
- Occlusion Management
- Backgroung Texture Access
- Intermediate programing in C#
- Blender 3D / Maya 3D / Photoshop Basic
- Handle Unity 3D/2D assets basic
- Hololens SDK development basic
- App Development Publish
Projects – Level 3
(Real-time Projects) – DURATION 300 HOURS
- Project Concept and Real world applications
- Architecture Planning
- Blender 3D / Maya 3D asset development
- Unity 3D Assets
- Unity 3D C# scripting and project development
- App development for Hololens
- Testing and Debugging
- Publish on store
6 Months Course/ 3 Months Project Work – 4 Hours per day
Level 0 | XR Foundation | 60 Hours | 15 days |
Level 1 | XR Intermediate | 300 Hours | 100 days |
Level 2 | XR Advanced | 400 Hours | 100 days |
Level 3 | Projects/ Trainee | 360 Hours | 90 days |
Eligibility
- Bachelor’s degree + exposure on programming(industry experience is a plus)
- Age should be below 30.
Curriculum
S. No | TOPIC | DURATION | CUMULATIVE No. OF DAYS |
1 | PROGRAMMING IN PYTHON • Introduction to Python, IDLE • Control flow • Functions • Lists, Tuples and Dictionaries | 5 days 1 day examination (objectives type + practical) | 6 |
2 | INTRO’ TO STATISTICS Errors & scales of measurements, Presentation of data, Measures of variations & central tendency, correlation & regression, probability & hypothesis, Exploratory Data Analysis, parametric & Non-parametric tests | 2 days | 8 |
3 | LINEAR ALGEBRA REVIEW • Matrices & Vectors • Matrix Vectors Multiplication • Matrix, Matrix Multiplication • Inverse and Transpose | 2 days | 10 |
4 | ANACONDA EXPLORER Using python (following topics) Data pre-processing • Importing the dataset • Missing data • Outlier Detection • Categorical Data • Splitting the dataset into the training set and test set. • Feature scaling | 4 days | 14 |
5 | REGRESSION 5.1.1 Simple Linear Regression… 5.1.2 Simple Linear Regression in python….. 5.2.1 Multiple Linear Regression.. 5.2.2 Multiple Linear Regression in python….. 5.3.1 Polynomial Regression…… 5.3.2 Polynomial Regression in python….. 5.4.1 Decision Tree Regression…. 5.4.2 Decision Tree Regression in python… 5.5.1 Random Forest Regression.. | 4 days 1 day examinaton (Objective type + practical) | 19 |
6 | CLASSIFICATION 6.1.1 Logistic Regression… 6.1.2 Logistic Regression in python… 6.2.1 K-Nearest Neighbours (K-NN)…. 6.2.2 K-NN in python…. 6.3.1 Support Vector Machine (SVM)… 6.3.2 SVM in python… 6.4.1 Kernel SVM…. 6.4.2 Kernel SVM in python… 6.5.1 Naive Bayes…. 6.5.2 Naive Bayes in python… 6.6.1 Decision Tree Classification… 6.6.2 Decision Tree Classification in python… 6.7.1 Random Forest Classification…. 6.7.2 Random Forest Classification in python… 6.8.0 Evaluating Classification Models Performance… | 5 days 1 day examination (Objective type + practical) | 25 |
7 | CLUSTERING 8.1.1 K-Means Clustering…. 8.1.2 K-Means Clustering in python… 8.2.1 Hierarchical Clustering… 8.2.2 Hierarchical Clustering in python | 3 days | 28 |
8 | INTRO’ TO DEEP LEARNING 8.1.1 Artificial Neural Networks.. 8.1.2 Artificial Neural Networks in python… | 4 days | 32 |
9 | DATA PRE-PROCESSING CONTD. DIMENSIONALITY REDUCTION 9.1.0 Principal Component Analysis (PCA)… 9.1.2 PCA in python… 9.2.1 Linear Discriminant Analysis (LDA)… 9.2.2 LDA in python.. | 2 days | 34 |
10 | BIG DATA TECHNOLOGY Distributed computing & big data, lot data Acquisition, Big Data Management, Data aggregation, Big data processing with database and programming concepts | 3 days | 37 |
11 | Hadoop, Hive, No SQL | 3 days 1 day examination | 41 |
12 | Java script | 4 days 1 day examination | 45 46 |
13 | Programming in R | 4 days 1 day examination | 50 51 |
14 | R Studio Using R (following topics) Data Pre-processing • Importing the dataset • Missing Data • Outlier Detection • Categorical Data • Splitting the dataset into the training set and test set. • Feature Scaling | 2 days | 53 |
15 | REGRESSION 15.1 Simple Linear Regression in R 15.2 Multiple Linear Regression in R 15.3 Random Forest Regression in R | 2 days 1 day examination (Objective type + practical | 55 56 |
16 | CLASSIFICATION 16.1 Logistic Regression in R… 16.2 SVM in R…. 16.3 Kernel SVM in R… 16.4 Random Forest Classification in R… | 3 days 1 day examination (Onjective type + practical | 59 60 |
17 | CLUSTERING 1. K-Means Clustering in R.. 2. Hierarchical Clustering in R… | 2 days 1 day examination | 62 63 |
18 | INTRO’ TO DEEP LEARNING IN R 1Artificial Neural Networks in python… | 1 day | 64 |
19 | DATA PRE-PROCESSING CONTD. DIMENSIONALITY REDUCTION 1. PCA in R 2. LDA in R… | 2 days | 66 |
20 | Final examination | 2 days | 68 |
21 | Final Project Evaluation | 2 days | 70+10 |